Help PhDs to kick-start careers in industry | Co-Founder and CEO @Alma.me | Building a bridge between academia and industry | Speaker | Scientist

Welcome to my profile!

I'm Elena, passionate about helping PhDs kickstart fulfilling careers outside of academia, and connect them with industry relevant positions. 

During my PhD journey, I realized that many PhDs face challenges transitioning from academia to industry. This difficulty often arises due to a lack of knowledge about potential positions, how to craft a resume for the industry, and prepare effectively for a job in that sector.

I've experienced this struggle firsthand. While pursuing my PhD, I felt lost. I knew that I no longer wanted to work in the lab; instead, I wanted to work with people, as that's where my passion lies. I went on my own discovery journey on "what is next".  I focused on the things I loved doing and thought of possible career options- after I identified what is next- I started working toward it by building a network in that area. 

Who am I, and how did I get here?

I recently graduated with a PhD in Medical Sciences from the Karolinska Institutet in beautiful Stockholm. 
As a Co-Founder and CEO of Alma.me my vision is to bridge the gap between academia and industry by providing information to help PhDs understand the array of opportunities after completing their studies and recognise the value of their skills beyond academia. 

If you are a PhD-student, Postdoc or tenure and you want to make the transition into industry follow me for more career advice.


Elena Hoffer, PhD

64% of scientists in industry feel good about their careers. Only 42% in academia do

A 2021 Nature survey put a number on something many of us already felt - and the findings are still just as relevant today (Link to full article in the comments)

In a survey of over 3,200 working scientists:
📊 64% of researchers in industry feel positive about their careers.
📊 Only 42% of those in academia say the same.

That's not a small gap.

And it gets more stark:
30% of academics reported experiencing discrimination, harassment or bullying at work.

In industry? 
That number drops to 15%.

This isn't anti-academia. It's pro-PhD and Postdocs.

The PhD journey is genuinely tough - and the structure around it doesn't always make it easier.

But I share this data because I talk to PhDs every single week who feel guilty for wanting to leave.

Who think wanting better pay, more stability, or a healthier work environment makes them somehow less serious about science.

It doesn't!
Wanting those things makes you human.

And the data shows - most people who make the move don't regret it.

Your curiosity, your skills, your love of solving hard problems - none of that disappears when you leave the lab.

It just finds a new place to live.

Want to hear real stories from PhDs who made the move?

🎙️ Listen to my podcast PostPhDirections - on YouTube or Spotify. 
Link in the comments 👇

♻️  Share to help a friend 

Happy Thursday  💙

Help PhDs to kick-start careers outside of academia | CEO @Alma.me | Complementing universities services for PhDs & Postdocs to secure jobs outside academia | Speaker I Podcast Host @PostPhDirections

Nobody talked about money during my PhD.

Wanting a good salary and a stable life felt like something you weren't supposed to admit.

As if wanting financial stability somehow made you less committed to science.

I've met senior academics who had never negotiated a salary in their entire career. And I've met researchers who couldn't afford to live near their own lab.
This is a problem - and it's one that follows PhDs into their industry job search.

Most PhDs I work with significantly underestimate their market value.
So here's a reality check, based on Glassdoor data (US market):

📊  Median PhD salaries by sector:
Information Technology: $193K
Transportation & Logistics: $183K
Pharma / Biotech: $139K
Consulting: $138K

These are not outliers. 
These are medians.

A few things worth knowing before you walk into a salary conversation:

1. Your PhD counts as work experience. 3–5 years of independent research, project management, and communication. Don't let anyone tell you otherwise.

2. The first number you say anchors the negotiation. Research your market range on Glassdoor and LinkedIn Salary before any conversation.

3. Asking for more is expected. Most companies build negotiation into their offers. Not negotiating is often leaving money on the table.

4. If they ask what you want - let them go first. Try: "I'd love to understand the budgeted range for this role first." You'll either confirm your number is in range - or avoid anchoring too low before you even know what's on the table.

5. If you don't know the salary range - ask. It's completely professional to say: "Could you share the salary range for this position?" Most companies know it. And it saves both sides a lot of time.

Your PhD is worth more than you think.

♻️ Repost to help a PhD friend

Happy Friday 💛

Salary data source: Glassdoor, June 2024, based on 13,327 submitted salaries (US market)

Dear PhDs,
You're allowed to change your mind.

About your field.
 About academia. 
About what success looks like for you.

The path you chose at 22 doesn't have to be the path you walk at 32. Or 42.

Look at me - I built my entire career towards being a scientist. 
A girl from a village of 500 people who worked her way to a PhD at Karolinska Institutet. That was the dream.

And then at 33, I started a company to help other PhDs find their next step.
Nobody saw that coming. 
Least of all me.

Changing direction isn't giving up. 
It's growing up.
It's evolving.

And it takes more courage than staying put.

Happy Sunday 💙

Most PhDs have a LinkedIn profile.
Almost none of them know how to use the platform.

I know - because I was one of them.
I had a profile and a photo. 

And I thought that was enough.
It wasn't.

LinkedIn helped me build my entire career beyond academia. 

My company. 
My community. 
A following of 140K people.

All of it started with learning how to actually use this platform.

An during the career's week by Proteintech Group in collaboration with Alma.Me I'm sharing some of my best tips - for free.

As part of Proteintech's Careers Week 2026 I'll be covering: 
🟣 How to build a profile that makes recruiters come to you 
🟣 How to network on LinkedIn without it feeling awkward or transactional 
🟣 How to use it actively in your job search - not just passively

And there's a full week of other sessions too - resume and interviewing in industry (by Angela Priest) grant writing and more.

Free. 
Daily. 
One week.

📅 March 23–27 - I'm on Wednesday March 25 
🕘 9 am CST / 2 pm GMT / 3 pm CEST

Register your free spot at ptglab.com - link in the comments 👇

♻️ Repost to help a PhD friend who needs this

Happy Tuesday 💛

It was a Monday evening during my PhD. Late in the lab. I was taking skin biopsies.

And I thought to myself:
I don't want to do this anymore. Lab work felt so isolating to me.

And I was at my best when I could be creative and brainstorm with others in meetings.

And immediately after that thought came another one, even scarier:
But what can I do?

I didn't wait for the answer to come to me.
I went looking for it.

I started reaching out to PhDs who did their PhD at Karolinska Institutet - just like me - and who had moved into all kinds of different directions.

Research equity analysis. 
Management consulting. 
Marketing. 
Sales.

And what struck me wasn't just that they had made it work -it was how many different paths were out there.

That's the thing nobody tells you when you're still inside the lab:
The world outside academia is not a narrow corridor.
It's more like a city you've never explored.

And the best way to navigate it is to find the people who already know the streets.

I wish someone had told me this earlier.
So here's what I'd go back and say to myself:
🟣 Your PhD is not a job title. It's a toolkit. 
🟣 "Leaving bench work" does not mean leaving science. It means finding a different way to use it. 
🟣 The skills you built matter far more than the specific techniques you used. 🟣 You are not starting over. You are redirecting. 
🟣 The confusion you feel right now is not a sign you're lost - it's a sign you're growing.

If you're in that in-between place right now - where you know you want something different but can't quite see what yet just know that feeling is valid.

And it won't last forever. 

Happy Monday 🩷

One of the most powerful tools for landing your first industry job after your PhD is completely free.

It takes 30 minutes a week or every second week.

And most PhDs either don't use it - or they use it wrong.
I'm talking about coffee chats aka informational interviews.

Not cold emails asking for a job. Not transactional networking that makes your skin crawl. 
Just… a real conversation with someone who has already made the jump.

Here's what I learned from doing many of them myself (and watching PhDs use them to completely change their job search):

- They show you what's actually out there — beyond R&D 
- They give you information no job description ever will 
- They build your network before you desperately need one 
- And sometimes? They lead to things you never expected

One PhD we worked with came back to me after a coffee chat and said:
"Elena, you won't believe it. They offered to refer me."

Was that the goal? No. 
But it's what happens when you show up with genuine curiosity instead of an agenda.

I just dropped a full YouTube video on this 
- how to find people to talk to
- how to reach out (without getting ignored)
- what questions to ask
- and how to stay connected after.

If you're during your PhD or Postdoc and wondering what's next - this one's for you.

👉 Link in the comments 

Happy Saturday 🩷

undefined undefined

Dr. Elena Hoffer. Still figuring it out.

When I started my bachelor's - figuring it out. 
When I did my master's - still figuring it out. 
When I started my PhD - figuring it out. 
When I finished my PhD and became Dr. Elena Hoffer - still figuring it out. When I stepped into marketing, content, LinkedIn - figuring it all out in real time. 
When I started my own company Alma.Me at 33 - absolutely figuring it out. When we hired our first team members - figuring that out too.

And honestly? 
I'm still figuring it out every single day.

I'll never forget working in the pharmacy after finishing my degree.

We had customers with doctor titles. PhDs. 
And I would look at them with pure awe - "What must one accomplish to get that title?"

Growing up in Germany, titles carry real weight. Prestige. You've made it.
I looked up to those people.

15 years later I got my own degree - Dr. Elena Hoffer - I felt so proud. I felt so many things at once. But I also felt something I didn't expect.
I still felt like I was figuring it out.

And that's when something slowly clicked for me:
We spend our whole lives chasing the next thing - the degree, the title, the job, the promotion - telling ourselves that will be the moment we finally feel like we've arrived.

But the destination was never the point.
It's always been about the journey. 
About who you become along the way.

Titles don't change that inner feeling as much as we think they will.
What changes us is the growth, the people, the experiences we collect.

If you're in the middle of something hard right now - a PhD, a career transition, building something from scratch - you don't have to have it all figured out.

None of us do.

Happy Monday 🩷

Most PhDs don't talk openly about not wanting to stay in academia.

Not to their supervisor. 
Not to their colleagues. 
Sometimes not even to their closest friends in the lab.

Nature Magazine just released a podcast episode on exactly this - why leaving academia is still a taboo topic, even now.

And one thing from it resonated deeply with what I see every day working with PhDs.

Josh, a neuroscience director who left academia in 2020, said:
"I felt much more comfortable talking to people who had already left. I was more scared about having those conversations with my colleagues than I was about the transition itself."

I hear this often in my work with PhDs.

Some are just starting to explore opportunities beyond academia. 
Some have already made up their mind.

But both carry that decision quietly - alone, for months - because saying it out loud in the lab still feels like admitting failure.

This is a culture problem. 
Not a personal one.

I didn't leave academia because I stopped loving science. 
I left because the system no longer aligned with my values. 
I wanted a different lifestyle. 
A different working environment.

And those are good enough reasons to leave - even if you love science deeply.
And wanting that - wanting stability, wanting a life that fits you - is not something you should ever feel ashamed of.

♻️  Share to help a friend 

Happy Wednesday 💙

Two women. 
Different continents. 
One shared belief:
PhDs and Postdocs deserve better career support than what currently exists.

That's how Alma.Me started.

Angela brings 20+ years of hiring experience - she's sat in the rooms where the decisions are made. 
I bring the PhD journey - the uncertainty, the identity shift, the figuring-it-out-as-you-go.
Together, we built something neither of us could have built alone.

But here's what I want to share today - When we first started building Alma.Me, imposter syndrome hit me hard.

Who am I to do this? 
I thought I needed to know everything before I could build anything.

Then Angela said something that changed how I saw it all.
She's sat in rooms with CEOs and senior executives most of her career - and she told me: nobody has it fully figured out. Everyone is trying their best with what they have. Everyone is winging it a little.

That was the moment something clicked.
Being in a role - whether it's a job, a business, or a new career - doesn't mean knowing everything.

It means:
Being open to learning. 
Willing to fail. 
Humble enough to let the data guide you. 
And resilient enough to keep going anyway.

Honestly? 
It's not that different from science.

In research, you don't know the answer before you run the experiment. 
You follow the data. 
You adjust. 
You try again.

Business is the same. 
Life is the same. 

Nobody truly knows. 
Most of the time, we're all figuring it out as we go.
And that's not a weakness. That's how growth works.

And an important thing I've learned - Sometimes it's the naive ones who bring the freshest perspective.

Not knowing "how things are supposed to be done" means you're not limited by how they've always been done.

Some of the boldest moves come from people who didn't know they "couldn't" do it.

So to every woman reading this today - If you're waiting until you feel ready: you won't. Start anyway. Start now!

If imposter syndrome is telling you "who are you to do this?": everyone in that room is asking the same question. 
You belong there.

If you feel like you don't know enough yet: that's not a gap. 
That's your edge. 
Fresh eyes see what experience sometimes misses.

You don't need to have it all figured out.
You need to be open. 
Curious. 
Willing to learn, fail, and keep going.

That's not just what building a business taught me.

That's what I see in every single woman who dares to take the next step - in her career, her job search, her life.

You are more ready than you think. 💜

Angela has been my biggest supporter - and my biggest challenger when I needed it most. She accepts me for exactly who I am. And pushes me to grow beyond who I thought I could be.

Today I celebrate her. 💜

Who is a woman that has inspired you to keep going? Who is your Angela?

Drop her name in the comments - let's celebrate them today. 👇

Happy International Women's Day to every woman daring to build something - a career, a company, a life - on her own terms. 💜

3 PhDs. All of them had sent over 200 applications.
All of them had heard back from almost no one.

And all three came to us at Alma.Me saying the same thing.
"I don't know what I am doing wrong."

Here's what was going on - and what changed for each of them:

PhD #1 was an Economics PhD who got feedback during an interview that her communication style wasn't landing with the hiring team.

That stung.
But instead of ignoring it, she reached out to us.

We worked on how she told her story - how she interacted and enageed in the interview conversation.

She landed her next offer with what the hiring manager called a "sweetheart deal." And she was specifically complimented on her communication.

PhD #2 too academia and did not receive any interview invitation after +200 applications.
We revamped the resume and taught her how to reach out to hiring managers directly.

Her response rate went from basically 0% to over 10%.

PhD #3 was getting interviews. But losing them.
He knew his research inside out.

What he hadn't learned was how to talk about it in a language that made a hiring manager lean forward.

We worked on how he framed his story.

He landed his role within 33 days of joining our program.

Here's the thing:
The problem was never the PhD.
The missing link was learning how to market themselves to an industry audience.

If you're stuck in the same loop - we take two PhDs a week into our program.

Link in the comments 👇

♻️ Repost to help a PhD friend

Happy Tuesday 💛

Everyone who thinks LinkedIn is a waste of time hasn't used it to its fullest.

I say this as someone who once during my PhD scrolled past it thinking - what's the point?

And then LinkedIn gave me:
A co-founder (thankful everyday for Angela Priest) 
A team. 
A podcast full of incredible humans. 
And friendships I didn't see coming.

One of those is Philipp Baaske.
Fellow PhD. 
Fellow founder. 
And honestly - my kind of people.

Successful, kind, and humble. 
That combination is rarer than it should be.
I read his book - The Honorable Entrepreneur - and I really loved it.
Not the kind of book that makes you feel like everyone else has it figured out except you.
Raw, honest, real. 

He writes about building a business the way it actually feels - the highs, the 
lows, the moments where you genuinely don't know if it's going to work out.

If you're a founder, a PhD, or just someone looking for an inspiring story told without the filter - read it.

Yesterday, I finally got to meet Philipp in Munich for dinner.

Great conversation. 
And yes - I finally got my signed copy. 

None of this happens without LinkedIn.
Was it uncomfortable in the beginning and a ton of work (and still is ;))? 
Absolutely.

Would I do it again every single day? 
Yes - without question. 

Philipp has been on my podcast PostPhDirections sharing his journey from PhD to founder. If you haven't listened yet, go find it.

And if you're ready to start your own LinkedIn journey -I'm sharing my best tips on LinkedIn networking and job searching at Proteintech Group's Career Week, in collaboration with Alma.Me.

It's free. Join us. 🎉

Registration link in the comments 👇 

You genuinely don't know who is one connection away. 

Happy Wednesday 🩷

Most PhDs I talk to have the same reaction when I mention networking:
"I'm not good at that." 
"It feels fake." 
"I wouldn't even know where to start."

Academia does not necessarily train you on this. 
You're trained to let your work speak for itself. 
To publish. 
To present data. 
To be rigorous.

Not to send a message to a stranger on LinkedIn and start a conversation.

But here's the truth:

The job market doesn't work the way academia does.

Many roles are filled through networks. Through people who know people. Through a conversation that happened months before a job was even posted.

Networking isn't about being loud or salesy.
It's about being visible, being human, and building real  relationships.

One of the PhDs in our program landed 3 interviews in a single day.

Not from applying to 3 jobs.
From 1 referral from a friend. 
From 1 referral from a new connection he'd met online. 
From 1 cold application - followed up with a direct message to the hiring manager.

That's what increasing your "luck surface area" actually looks like.
And the crazy part of my own story (most don't know) ?

Alma.Me only exists because I networked on LinkedIn.

Angela Priest - my co-founder, with 20+ years of hiring experience - I met her here. One conversation that literally changed the trajectory of my entire professional life.

If you're a PhD who thinks networking isn't for you (btw, it's outside most peoples  comfort zone - you are not alone) -  I'd invite you to reconsider.

Not because it's easy.
But because it works.

🎙️ I talked about this in the very first episode of my podcast PostPhDirections - with Angela herself. How we met, why networking matters, and what it really looks like in practice.

Listen here: https://lnkd.in/dPHrxGVv

Happy Thursday  🩷

This photo was taken at the networking session I organised as part of the PhD course I ran at Karolinska Institutet. By the way, we are running it again - registration opens tomorrow. 
Best part? 
You get ECTS points and it counts towards your PhD degree 😉
Stay tuned if you are a PhD student at KI, or another Swedish or European university (open to all -but limited slots).

I used to think leaving academia meant starting over from zero.
That's what it felt like.

Years of training. Papers. A PhD thesis I was genuinely proud of. 
And then the thought of leaving felt like throwing it all in the bin. 

Like: "If I leave, was it even worth it?"

I've spoken with so many PhDs who feel exactly this. The sunk cost. The guilt. 

But here's what I've learned since leaving:
You don't start over. 
You start differently.

Everything you built in academia – the rigor, the resilience, the ability to sit with uncertainty for years and still push forward – that goes with you.

It doesn't disappear when you leave the lab.
It shows up in how you approach problems. 
In how you learn fast in new environments. 
In the way you think.

I didn't start over when I left.
I started Alma.Me.

And I built it from exactly the skills I thought were "only academic."

If you're in that place right now – wondering if leaving means losing everything you worked for – I promise you. It doesn't.

If you're at a point where you're questioning whether your path is still yours - listen to my podcast episode with Armando Cázares-Körner.

He left academia with a Science paper. Science! He had every credential to build a successful academic career - and he still chose something different.

It's one of the most inspiring conversations I've had. 

🎙️ Listen to the full episode: Link in the comments 👇 

Happy Monday 🩷

Dear PhDs 

Every conversation you have is building your network.

Every application teaches you something about what you want.

Every interview makes you better at the next one.

Even when it feels like nothing is happening, you're moving forward.

Trust the process.

Happy Sunday 💙

Most PhDs spend months sending applications into the void.

No feedback. No idea what's going wrong. And they often experience just silence or rejection.

Here's is the things the resume is often the first thing that kills your chances.
Not your skills. 
Not your experience. 
Your resume.

And the frustrating part?
You don't know what a hiring manager actually sees when they open it.
That's exactly why Angela Priest and I created the Resume Review - Live session.

Angela has 20+ years of hiring experience.
She has been on the other side of the table - literally deciding who moves forward and who doesn't.

On March 12th at 6PM CET / 10AM MST, she's going to show you:

🔍 What hiring managers look for in the first 10 seconds 
❌ The most common mistakes PhDs make (and don't even realize) 
✅ How to fix them - live, in real time

This is part of our PhD-to-Industry Ready Series - free live events designed to give you the information you actually need to make your transition work.

No fluff. No "just believe in yourself" advice. Real feedback. Real fixes.

👉 Sign up link in the comments or scan the QR code 

♻️  Share to help a friend 

Happy Friday 🩷

Your academic CV is costing you interviews.

Most PhDs don't realise this until they've sent 100+ applications and heard almost nothing back.

And the frustrating part?

It's not your skills. 
It's not your experience. 
It's how you're presenting them.

A 4-page academic CV that leads with publications and conference talks tells a recruiter almost nothing about what you can actually do for them.

Here's what I see again and again: 
🟣 PhDs describing what they studied - not the outcomes they created 
🟣 Resumes written for an academic audience - not a hiring manager 
🟣 Brilliant candidates getting filtered out before anyone even reads their story

That's why I'm so glad my co-founder of Alma.Me -  Angela Priest is speaking at Proteintech Group's Careers Week 2026.

Angela has 20+ years of hiring experience. She has sat on the other side of the table hundreds of times. She knows exactly what makes a resume get read - and what makes it get ignored.

On Tuesday she's running a live Industry Resume Writing Workshop - for free.
🟣 What hiring managers actually look for 
🟣 How to translate your research into business language 
🟣 How to go from academic CV to industry resume that gets responses

📅 Tuesday March 24 
🕘 9 am CST / 2 pm GMT / 3 pm CEST

Register your free spot: https://lnkd.in/d5-DaDnN

♻️ Repost to help a PhD friend in need

Happy Saturday 💛

Dear PhDs,

Rest is not the enemy of progress.

It just feels that way when you’ve been trained to measure your worth in output.

More papers. 
More experiments. 

But some of the best ideas - the clearest thinking, the boldest decisions -  don’t come from pushing harder.

They come from stepping back.

Give yourself permission to rest this Sunday.

It’s not time wasted.
It’s time invested.

Happy Sunday 🩷

The job market in 2026 is shifting. Here's why that might actually be good news for PhDs --> learn here how to position yourself best

Angela Priest has 25+ years of industry experience (20 in hiring )- she's seen market shifts come and go.

And she sat down with me to break down exactly what's happening right now.
Because there are real shifts - and some of them are actually working in your favour as a PhD.

In our latest episode of PostPhDirections we talked about:
🟣 What's actually happening in hiring right now (and why uncertainty is becoming "the new normal" for companies)
🟣 Why entry-level jobs aren't disappearing - they're just changing shape
🟣 The roles with the highest demand for PhDs right now (hint: data fluency is your secret weapon)
🟣 The one skill listed in 85% of all job ads - and what companies actually mean by it (it's not what most PhDs think)
🟣 The one unspoken hiring criteria that almost no article will tell you about

And my personal favourite part of the conversation?
Angela said something that I think every PhD needs to hear:
"PhDs assume that the people they're competing against have the same level of skill. They don't."

You have more than you think.
You just have to learn how to say it.

🎙️ New episode is out now - link in the comments 👇

Happy Sunday 💛

59 - Learning German and getting a driver's licence.

I love this so much.

Because we spend so much time thinking we've missed our window. 
Too late to switch. 
Too senior to start over. 
Too established to take a risk.

But this post is proof that there is no such thing as too late.
I left academia at 33 and built a company from scratch. 
First in my family to do it. 
No roadmap. 
No guarantee.
Just a decision.

If you're a PhD sitting on the fence about making your move into industry - let this be your sign.

The window is open. 
It always is.

Dare to take the step. 

Happy Monday 🩷

Academic leadership training I Professor of NeuroImmunotherapy l Dean of Doctoral Education l Empowering professional leadership and shaping PhD education l Have trained 8000+ PhD supervisors l #MADBob

At age:
18 - I left home for University
21 - I finished my B.Sc
24 - I finished my PhD
27 - I moved to Sweden
28 - I learnt to speak Swedish
31 - I became an Associate Professor
33 - I became a research group leader
39 - I became Study Director in my department
42 - I became Central Study Director at the university
47 - I became a Professor
48 - I won the KI prize for pedagogy
53 - I became Dean of Doctoral Education
58 - I won the FEBS Education award
59 - I learnt to speak German
59 - I got my driver’s licence
 
What is my view on all this?
 
·     LIFELONG learning means learning throughout your life – there is always something new to learn.
·     Some things you wait longer for than you think you should.
·     Some things happen when you think they should, or even faster.
·     Some things surprise you.
·     Each step is a step forward, a new experience.
 
Don’t spend time looking back with regret – your history is already written forever.

Don’t only focus on where you are today – it won’t get you anywhere long-term.

Don’t look to the future with fear of the unknown, but rather with peaceful anticipation.
 
Follow this discussion of doctoral education via #MADBob
If you are interested in personal or group leadership training for academic supervisors/leaders, check out my website. I have taught over 8000 supervisors to date.

#MADBob #PhDsupervision #AcademicLeadership #DoctoralEducation #ResearchLeadership

A Psychology Postdoc we worked with expected $70-80K for her first industry job and she landed one for $150K.

She had two years of postdoc experience. She came to us knowing she wanted industry.

She just had no idea what she was actually worth.

Her number in her head?
$70–80K 

That felt "realistic" to her.

That felt like what a postdoc jumping into industry could ask for. 
We see this so often. During a Postdoc you often make around 60K, and 80K feels like a realistic increase in salary. 

PhDs who have spent years in an environment where salaries are fixed, low, and non-negotiable:

They  carry that ceiling into their industry job search.
They don't know what the market actually pays.
They  don't know how to negotiate.
They don't know that their skills are genuinely scarce and genuinely valuable.

So they undersell themselves before they've even started.
What changed for her:
- We showed her what roles at her level were actually paying 
- We worked on how she positioned her experience in interviews 
- We helped her to get confident that her skillset is worth more than 80K

She landed a Senior Data Scientist offer for $150K (US salary).
Nearly double what she thought she could ask for.

This is what happens when you finally operate with the right information.

We take two PhDs a week into the Alma.Me Job Accelerator Program.
If you're ready, apply here: https://lnkd.in/dwhAW8xQ

♻️ Repost to help a postdoc know their worth

Happy Friday 💙

I help PhDs, Postdocs & Lecturers secure tenure-track jobs and navigate academia | Insider knowledge tips on how to succeed | Academic Career Mentor | Professor & Research Director

I was a lost PhD student. Confused. Overwhelmed. Ready to quit.

Sitting in my tiny office at 2 AM, drowning in research papers, I made a promise...

"If I somehow make it through this, I'll help others navigate what I'm struggling with."

Today, I'm a Professor at a top UK university.

But here's what matters more...

I've kept that promise by helping researchers complete their PhDs and navigate academia.

------

The brutal truth about doing a PhD/DBA whilst working

I hear the same struggles from the 26% of PhD & DBA students who are working professionals:

→ I can't keep up -the mental capacity is exhausted
→ I'm juggling three full-time jobs with no bandwidth
→ I've been stuck for 3-6 months with no real progress
→ My family thinks my PhD/DBA is a hobby, not a second job
→ I feel isolated - no one understands what I'm going through

Sound familiar? You're not alone. And it's not your fault.

Universities train PhD/DBA researchers for academia, but working professionals need something completely different:

❌ You're investing $25-80K but risk joining the 33% who drop out
❌ Motivation crashes after major life events (births, job changes, pandemic)
❌ Distance learning leaves you isolated, struggling to navigate systems alone
❌ You don't have 40 hours/week; you have 10 hours scattered across nights & weekends  
❌ Your supervisor gives great academic feedback but doesn't understand work-life-PhD balance

That's why I created specialised services for serious researchers.

My transformation:

→ 30+ PhDs/DBAs mentored to success
→ 130+ publications across top journals
→ £9 million in research funding secured
→ From PhD uncertainty to Professor by 40
→ 230K researchers follow my guidance daily
→ Research reached 30+ million people globally

FREE RESOURCES:

✅ Weekly newsletter (10K+ subscribers) www.phdtoprof.com/newsletter
✅ Free academic resources www.phdtoprof.com/store
✅ AI tools for ethical research productivity

PREMIUM SERVICES:

🎯 Premium PhD/DBA Mentoring - For senior professionals completing their PhD/DBA on time
🎯 PhD/DBA Proposal Development - Support developing and passing proposals
🎯 Expert Thesis Review - Comprehensive dissertation feedback from an experienced PhD examiner
🎯 AI in Research Masterclasses - Responsible and ethical AI use for researchers
🎯 University & Institution Training - Workshops on responsible AI in research for academic teams

My mission:

Help you complete your PhD/DBA on time while using AI responsibly in your research.

Academic success doesn't have to be a mystery. You just need the right guide.

Emmanuel Tsekleves

I've examined 45+ PhD theses. I ask the same 10 questions every time. Most candidates stumble on question 3. Here's what they are and how to answer each one.

Last year, a strong candidate walked into her viva with a thesis I genuinely admired. Solid methodology. Clear contribution. Well written.

Then I asked question 3. She froze.

This happens more often than you think. 
Not because candidates are unprepared. 
Because nobody tells them what examiners are actually testing.

Here are the 10 questions I ask in every examination.

1. "Can you summarise your thesis in 3 sentences?" 
I'm testing clarity of thought. 
If you can't distil your work, you don't fully understand it yet.

2. "What is the original contribution of your research?"
I'm testing whether you know what makes your work matter. 
Many candidates undersell this.

3. "Why this methodology and not an alternative?" 
This is where most fail. 
They chose their methodology because their supervisor told them to. 
Not because they understood why. 
Examiners notice immediately.

4. "What are the limitations of your study?" 
I'm testing intellectual honesty. 
If you say "none," I worry.

5. "How does your work relate to [specific paper in your field]?" 
I'm testing depth of literature knowledge. 
I pick a paper from your reference list. 
If you can't discuss it, I know you haven't read it properly.

6. "If you could start again, what would you do differently?" 
I'm testing reflective capacity. 
The best answers show growth, not regret.

7. "How would you respond to [specific critique of your approach]?" 
I'm testing your ability to defend under pressure. 
Stay calm. Acknowledge the point. 
Then explain your reasoning.

8. "What are the practical implications of your findings?" 
I'm testing real-world relevance. 
If your research has no application beyond the thesis, that's a problem.

9. "How does your theoretical framework connect to your data analysis?" 
I'm testing coherence. 
The strongest theses have a clear thread from philosophy to findings.

10. "What should be the next study after yours?" 
I'm testing forward thinking. 
If you can't answer this, you haven't thought beyond your own submission.

Question 3 catches the most candidates because choosing a methodology is the single most important decision in your PhD. 
And most students never learn to justify it.

Which question would catch you off guard?

Save for your viva prep.

Repost to help a PhD student preparing for their defence.

#PhDViva #PhDExamination

I've created a full viva preparation guide with model answers for each of these 10 questions. Available in my newsletter this week. Register for free to access it: https://lnkd.in/ezkxz2m2

I help working professionals complete their PhD/DBA/EDBA on time | Professor | 45+ PhD Theses Examined | Follow for posts on Research Skills, AI in Research & Academic Career Success

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Most PhD supervisors will never tell you this. The real reason PhD students fail.
It is not methodology. It is not data. It's...

It is that they never clearly identified a research gap

I had a student last year who spent 8 months reading
But when I asked her one question, she went silent

"What is actually missing from this literature?"

She could tell me everything researchers had found
But she could not tell me what they had missed

This is the most common problem I see
Students describe the research
They never identify the gap

So I started teaching the 7 types of research gaps:

1. Evidence Gap
No study has investigated this topic, population, or context at all.
The simplest gap. The literature is simply silent.

Where to start: Search for your topic plus a specific population or setting. If nothing comes up, you may have found an evidence gap.

2. Knowledge Gap
Studies exist, but they have not explained why something happens.
We know the what. We do not know the why.

Where to start: Look for studies that report findings but call for further investigation into the underlying mechanisms.

3. Practical Gap
Research exists in theory but has not been applied or tested in practice. 
The gap sits between what we know and what we do.

Where to start: Compare academic literature with industry reports or professional guidelines. Where do they disconnect?

4. Methodological Gap
The topic has been studied, but only using one approach.
A different method could reveal different insights.

Where to start: If every study in your area uses surveys, there may be a methodological gap for qualitative or experimental approaches.

5. Theoretical Gap
No existing theory adequately explains the phenomenon.
Current frameworks do not fit the data.

Where to start: Look for studies where researchers say their findings were "unexpected" or "inconsistent with existing theory."

6. Empirical Gap
A theory exists but has never been tested with real data, or has only been tested in one context.

Where to start: Find well-cited theoretical papers and check whether they have been empirically validated in your context.

7. Population Gap
Research exists but only covers certain groups, regions, or industries.
Your population has been excluded.

Where to start: Check the sample descriptions in key studies. If they all use the same population, every other group is a potential gap.

The secret most supervisors do not teach: the strongest research questions combine two or more gap types.

Evidence gap plus population gap: "No study has examined X among Y."

Methodological gap plus knowledge gap: "Using interviews instead of surveys to understand why Z happens."

One gap gives you a research question.
Two gaps give you an original contribution.

Which gap type fits your research area best?

Want the high-res PDF poster? Subscribe to my newsletter.

Save this for when you write your literature review.
Repost for a colleague still searching for their topic.

#ResearchGaps #PhDTopic

How I taught my PhD students to turn boring abstracts into reader magnets.
One of my mentees had submitted to 4 conferences before we started working together. Rejected from all 4. Here's how we fixed it: 

His research was solid. His methods were rigorous. His results were genuinely interesting.

But his abstract read like a methods section. Dense. Flat. Forgettable.

In our first session, I restructured his abstract using the same 6-step framework I teach every researcher I mentor.

Same research. Same results. Different structure.

He resubmitted to a conference the following month.

Accepted first time.

The framework is simple:

1) Start with relevance. Make the reader care in the first sentence.

2) Define the gap. Show why your study is necessary.

3) Clarify your aims. Leave no doubt about your direction.

4) Summarise your approach. Establish credibility in one line.

5) Highlight your discoveries. Lead with your most important result.

6) Explain the impact. End with why it matters.

Most abstracts fail because researchers try to summarise everything.

Strong abstracts do the opposite. They make reviewers curious enough to read the full paper.

His research didn't change. The way he communicated it did.

Every sentence in an abstract must justify its place.

I've broken down each step in detail in the visual below.

---

Which part of abstract writing do you find most challenging?

#AcademicWriting #PhDLife

I tested 12 AI writing tools over 3 months.
Here's which ones actually pass journal editorial standards.

A talented PhD student came to me in panic recently.

His manuscript was desk-rejected.

Not for weak science. For using an AI tool the wrong way.

The editor's message was blunt: "Evidence of undisclosed AI-generated content. Submission withdrawn."

One tool. One mistake. Months of research thrown away.

This is happening more than you think.

Journal editors are vigilant. They're testing submissions. They're catching mistakes.

After months of conversations with editors and tracking submission outcomes, I've identified a clear pattern:

Some AI tools are safe when disclosed properly.

Others will get your paper rejected instantly.

The difference comes down to one question:

Does the tool create content or does it check and organise your content?

Tools that check grammar, improve clarity, refine translations, or help you structure your arguments are generally accepted.

Tools that generate text, draft paragraphs, or produce content you pass off as your own will end your publishing career.

I've mapped all 12 tools I tested into two clear categories in the visual below.

Green means editors accept it with proper disclosure. Red means it puts your career at risk.

The rule I teach every researcher I mentor:

If AI creates content, always disclose it.
If it checks or organises, you're generally safe.
When uncertain, err on the side of caution.

No shortcut is worth your reputation.

Academic integrity is non-negotiable.

---

Which AI tool have you found most useful in your writing process?

#AIinResearch #AcademicWriting

Writing Guides

Ready for more? 

Join my exclusive weekly Academic Pathfinder newsletter where I share the exact strategies that have helped hundreds of PhDs finish their PhDs on time, secure competitive tenure-track positions and thrive in academia. 

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Newsletter

Ready for more? 

Join my exclusive weekly PhD Insider newsletter where I share the exact strategies that have helped hundreds of PhDs finish their PhDs on time, use AI responsibly in Research and thrive in academia. 

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👉 Try for free: https://www.bohrium.com/?utm_source=oversea&utm_term=emmanuel&utm_campaign=kol

PhD 1:1 Autoplug 1 (Form-directed)

Doing your PhD while working full-time is lonely.

Your supervisor is juggling 12+ students. They don't understand how it feels to squeeze research into exhausted evenings and weekends. You get vague feedback like "needs more depth" with no clear direction. Months pass. You start wondering if you'll ever finish.

I've mentored 30+ mid to senior professionals through this exact struggle to successful completion.

20 years at a top 1% university. 25+ PhD examinations. I know where you're losing time.

I take on a small number of dedicated professionals for private premium 1:1 mentorship.

Interested? Start here: https://forms.gle/L3wuDxfAgvDA17SD8

1:1 mentoring Autoplug 2 (Form-directed)

Ready for more? 

Join my exclusive weekly Academic Pathfinder newsletter where I share the exact strategies that have helped hundreds of PhDs finish their PhDs on time, use AI responsibly in Research and thrive in academia. 

Get Wednesday's insider tactics delivered straight to your inbox: https://phdtoprof.com/newsletter

1:1 Mentoring Autoplug 3 (DM-directed)

You're trying to do three jobs at once: career, family, PhD.

Your supervisor has never lived that reality. I have spent 20 years mentoring professionals who have.

Private premium 1:1 mentorship for mid to senior professionals serious about finishing. Limited availability.

Interested? Start here: www.phdtoprof.com


1:1 Mentoring Autoplug 4 (DM-directed, shortest)

Feeling behind on your PhD? Supervisor too busy to help? Wondering if you'll ever finish?

I provide private premium mentorship for mid to senior working professionals. 1:1 support. Limited spots.

DM "MENTORSHIP" with your situation.


Proposal development

Writing your upgrade proposal while working full-time is a different kind of hard.

Your supervisor is juggling 12+ students. They don't understand how it feels to squeeze proposal writing into exhausted evenings and weekends.

You get vague feedback like "needs more depth" with no clear direction.

Your upgrade deadline approaches. You start wondering if you'll even pass.

I've mentored 30+ mid to senior professionals through this exact struggle to successful completion.

20 years at a top 1% university. 40+ PhD examinations. I know where you're losing time.

I take on a small number of dedicated professionals for private premium 1:1 mentorship.

Interested? Start here: www.phdtoprof.com

Academic Writing

Writing your PhD while working full-time makes this ten times harder.

Your supervisor gives feedback like "needs better flow" with no clear direction.

You rewrite the same paragraph five times after a 10-hour workday.

You wonder if your English is good enough. If your arguments are strong enough. If you'll ever get published.

Frameworks and free guides help. But they can't give you personalised feedback on your specific writing.

I've mentored 30+ mid to senior professionals through this exact struggle to successful completion.

20 years at a top 1% university. 40+ PhD examinations. 130+ publications.

I know where your writing is losing marks. And I know how to fix it fast.

I take on a small number of dedicated professionals for private premium 1:1 mentorship.

Interested? Start here: https://forms.gle/L3wuDxfAgvDA17SD8

1:1 Mentoring

Choosing between an MBA and a DBA is one of the biggest decisions a working professional can make.
 
The wrong choice costs you 3 to 5 years and tens of thousands of pounds.
 
I've supervised both. I know which path fits which person.
 
I take on a small number of dedicated professionals for private premium 1:1 mentorship. From choosing the right programme to completing your doctorate on time.
 
Interested? Start here: https://www.phdtoprof.com

Lead magnet

If you're struggling with your PhD right now, I've put together the exact milestone planning template I used with this student. Link in my newsletter

Store

I've expanded this into a full downloadable guide with annotated examples for each level of the funnel.

You can get it from here:  https://phdtoprof.com/store

If you found this framework useful, I've created a library of free and paid guides for every stage of your PhD.

Literature review templates, thesis chapter outlines, methodology decision trees, and more.

Browse the full collection here: https://phdtoprof.com/store


Newsletter 2

Posts like this one scratch the surface. Every Wednesday I go deeper.

One insider technique to complete your PhD on time, sharpen your research skills, and use AI responsibly. In under 4 minutes.

Join 10,000+ researchers getting my free PhD Insider newsletter: https://phdtoprof.com/newsletter

Resources

Here are the links to all 8 courses:

Understanding Research Methods, University of London: www.coursera.org/learn/research-methods
Qualitative Research Fundamentals, Yale University: www.youtube.com/watch?v=wbdN_sLWl88
Writing in the Sciences, Stanford University: www.coursera.org/learn/sciwrite
Introduction to Systematic Review, Johns Hopkins University: www.coursera.org/learn/systematic-review
How to Write and Publish a Scientific Paper, École Polytechnique: www.coursera.org/learn/how-to-write-a-scientific-paper
Research for Impact, University of Cape Town: www.coursera.org/learn/research-for-impact
Persuasive Writing and Public Speaking, Harvard University: pll.harvard.edu/course/rhetoric-art-persuasive-writing-and-public-speaking
Data Analysis: Visualisations in Excel, The Open University: www.open.edu/openlearn/science-maths-technology/data-analysis-visualisations-excel/

For more curated resources like this, join 10,000+ researchers in the free PhD Insider newsletter: www.phdtoprof.com/newsletter

Sponsored 2

My first 5 grant applications were rejected. Every single one. 
Here's how I went from £10k to £10m in research grant funding:

I remember opening that fifth rejection email and thinking maybe my research just wasn't good enough. 
Maybe I wasn't cut out for this.

Then a panel reviewer told me something that changed everything. 
She said: "I stopped reading on page 2."

Not because the science was weak. 
Because the way I presented it was.

I had buried the real-world impact on page 3. 
I led with the literature gap instead of the problem. 
My methodology was sound but my narrative was invisible.

I was writing for academics. I should have been writing for funders.

So I rebuilt my entire proposal structure around three principles. 

I now call it the 3P Proposal Structure.

P1: Problem Framing. Lead with the real-world problem and its cost. 
Not the gap in the literature. 
Funders don't fund gaps. 
They fund solutions. 
"This problem costs the NHS £2.3 billion annually" hits harder than "this area remains under-explored."

P2: Path Innovation. 
Show what you will do differently. 
Not just what you will study. 
Every applicant studies something. 
Very few explain why their approach is the one that will actually work.

P3: Projected Impact. 
Connect your outcomes to the stakeholders who fund research. 
If the funder can see themselves in your story, you win.

Same research question. 
Completely different proposal structure. 
The next application secured half a million pounds.

Then a million. Then over the course of my career, more than £10 million in research funding.

Grant writing is storytelling. 
Your research is the plot. 
The funder needs to see themselves in the story.

What's the most frustrating feedback you've received on a grant application?

Save this framework.

Repost for anyone applying for funding.

#GrantWriting #AcademicFunding

45 PhD theses later, I can spot a weak lit review in 30 seconds. 
Every strong one follows this framework

After examining 45+ PhD theses, I noticed the same lit review structure in every strong thesis. 

And a completely different structure in every weak one.

I once had to tell a PhD student their literature review needed a complete rewrite. Six months of work. Gone.

The problem was not effort. It was structure.

Their review was a 40-page list of study summaries. "Fitzpatrick (2019) found this. Li et al (2025) found that." 

Forty pages of it. 
No themes. 
No argument. 
No gap.

I've seen this mistake in roughly 70% of the theses I examine. 
Students describe what others found. 
But they never explain why it matters or what is still missing.

So I created what I call the Examiner's Lit Review Framework. 
It works like a funnel.

Start wide. End focused.

Level 1: Broad context. What is the field and why does it matter right now?

Level 2: Specific area. What do we already know from the research?

Level 3: Critical gaps. What is missing, contested, or under-explored?

Level 4: Your contribution. How does your study fill that gap?

Every strong thesis I've examined follows this logic. 
The funnel forces you to move from description to argument. 
From "what exists" to "what's missing" to "why my study matters."

The rules are simple:

Synthesise by theme, not by author.
Group ideas, not studies.
Show how the field has evolved.
Always end with a clear gap statement.

And whatever you do, stop listing studies one by one. 
That's a bibliography, not a literature review.

That student I mentioned? She rewrote her review in 3 weeks using this framework. Her examiner called it exemplary.

Same researcher. Same topic. Same literature. Completely different result.

The structure made the difference.

What's the biggest challenge with your lit review right now? 
Drop it below.

Save this framework.
Repost for a colleague struggling with theirs.

#LiteratureReview #PhDWriting

I've expanded this into a full downloadable guide with annotated examples for each level of the funnel. See my comment below on how to access it.

Most PhD students are lied to about academic pay. 
The numbers are brutal, and almost nobody gets the real story.

I'm a Professor. I've seen the salary spreadsheets. 

The gap between what academia promises and what it pays would shock most PhD students.

Nobody told me the truth about academic pay when I started out.

They said the work was "rewarding." 
They said it was a "calling."

What they didn't say: a starting lecturer earns less than a mid-level project manager with half the qualifications.

A colleague left for industry last year. 
Same expertise. She doubled her income in month one.

Here's what bothers me most.

Universities use your passion as a negotiation tool. 
"If you really loved research, you wouldn't ask about money." 
I've heard versions of that in every institution I've worked at.

I'm not saying leave. I chose to stay. 
Intellectual freedom, shaping a field, mentoring the next generation. 
Those things matter.

But go in with your eyes open. 
Know the numbers before you commit.

Your passion is not a discount code.

Did anyone ever make you feel guilty for caring about pay in academia?

Save to compare later with industry jobs.

Repost to normalise this conversation.

#AcademicLife #HigherEducation

----
Disclaimer: These salary ranges are indicative estimates based on publicly available data from sources. Figures represent gross annual salaries for assistant professor or equivalent entry-level permanent academic roles. Actual salaries vary significantly by university type (public vs private, research-intensive vs teaching-focused), discipline, experience, contract type, and region within each country. 

These figures are not directly comparable across countries due to differences in taxation, cost of living, pension contributions, benefits packages, and purchasing power. UAE salaries, for example, are tax-free, which significantly changes the take-home picture. Exchange rates based on XE/Exchange-Rates.org (Feb 2026). 

This is meant as a starting point for conversation, not a definitive guide. If you have salary data from countries not listed here or corrections to share, please add them in the comments. The more transparent we are, the better.

Sources: ERI SalaryExpert (2025), Glassdoor (2025–2026), Academic Positions (2024), UGC 7th Pay Commission, India, University of Cape Town Pay Scales (2026)

I have reviewed hundreds of free online courses for PhD researchers. Most are not worth your time. These 8 are the ones I give every student I supervise.

No paywalls. No certificates required. Just the courses that actually make a difference.

A quick note: courses on Coursera can be audited free. Full content, no certificate. Click "audit this course" when you enrol.

Here they are.

1. Understanding Research Methods
University of London, Coursera

The clearest foundation course I've found. Covers the full methodology chain from philosophy to methods. If you're confused about how the pieces connect, start here.

2. Qualitative Research Fundamentals
Yale University, YouTube

A rigorous introduction to qualitative research from one of the world's leading universities. Free on YouTube. Essential if your study is interview or observation-based.

3. Writing in the Sciences
Stanford University, Coursera

The best academic writing course available free online. Works for any discipline despite the name. I recommend this to every student who tells me their writing feels unclear.

4. Introduction to Systematic Review and Meta-Analysis
Johns Hopkins University, Coursera

Essential for anyone doing a literature-heavy thesis. Covers the full process from search strategy to synthesis.

5. How to Write and Publish a Scientific Paper
École Polytechnique, Coursera

Goes beyond the thesis. Covers the full publication process. If you want your research to reach journals, not just examiners, this one matters.

6. Research for Impact
University of Cape Town, Coursera

The most underrated course on this list. Covers knowledge translation and real-world impact. Directly relevant to anyone navigating REF conversations or knowledge exchange in their institution.

7. The Art of Persuasive Writing and Public Speaking
Harvard University, Harvard Online

Academic argument and oral communication. More useful for viva preparation than most viva prep guides. Fully free, hosted directly on Harvard's platform.

8. Data Analysis: Visualisations in Excel
The Open University, OpenLearn

Practical and accessible. If you need to present findings clearly and data visualisation intimidates you, this is where to start. Fully free on OpenLearn.

Where I tell my students to begin: 
Start with course 1 to get your methodology foundations right. 
Move to course 3 early, before you start writing chapters. 
Add course 4 when you begin your literature review. 
Everything else depends on your specific research design.

Links to all 8 are in the pinned comment below.

Which of these have you already taken? And what would you add to the list?

Save this. Share it with your research group.

Repost to help a PhD student who needs it right now. #PhDResearch #AcademicWriting

graphical user interface, text, application, email

Poor writing kills more academic careers than bad research. Here's a guide that helped an international PhD student in our programme fix it:

An international PhD student in our programme had her paper rejected three times last year.

Each reviewer said the same thing: "The science is strong but the writing lacks clarity and structure."

Her research was publishable. Her writing wasn't.

She didn't need more data. She needed a system.

That's the problem most international researchers face.

Nobody teaches you how to write academically in English. You're just expected to figure it out.

Then I found a resource that changed how I support PhD students in our programme.

Education and Training Boards Ireland published a 94-page academic writing handbook.

Completely free. Completely systematic.

It breaks the entire writing process into 5 clear steps:

Getting started with planning and brainstorming. Drafting with proper argument structure. Reviewing for clarity and logic. Editing for grammar and precision. Presenting to professional standards.

What makes it different from generic writing advice?

It gives you self-assessment tools to spot weaknesses before reviewers do.

She used it to restructure her rejected paper.

Fourth submission. Accepted with minor revisions.

Same research. Same data. Better writing system.

Good academic writing isn't talent. It's a learnable process.

Especially when English isn't your first language.

Link to free download in comments.

---

Which writing step challenges you most: drafting, editing, or structuring arguments?

#AcademicWriting #PhDLife

I help working professionals complete their PhD/DBA on time | Professor | 45+ PhD Theses Examined | Follow for posts on Research Skills, AI in Research & Academic Career Success

She failed her viva. Her research was original.
The examiner asked: 'Why this research philosophy and not another?' She had no answer.

Not because she was a bad researcher.

Because nobody had ever explained how the pieces connect.

Three years of work. One question. No answer.

Your research methodology is not a menu.

It's a universe. And every layer connects to every other.

Your philosophy determines your approach. Your approach determines your methodology. Your methodology determines your methods.

Get the first layer wrong and nothing that follows makes sense.

Layer 1: Research Philosophy

Your worldview. What reality is and how we can know it.

Positivism. Reality is objective and measurable. Home of quantitative research, surveys, and hypothesis-testing.

Interpretivism. Reality is constructed. You cannot separate the researcher from the research. Home of interviews, ethnography, thematic analysis.

Pragmatism. Whatever best answers your research question. Mixed methods live here.

Critical Realism. Reality exists but we can only access it imperfectly. Common in health and complex social research.

Layer 2: Research Approach

Deductive: start with theory, test against data. Fits positivism.
Inductive: start with data, build theory. Fits interpretivism.
Abductive: move between both until something explains it. Fits pragmatism.

These follow from Layer 1.

Layer 3: Methodology

The logic behind your research design. Not the tools.

Grounded theory lives in interpretivism. Experimental design lives in positivism. Mixing them without justification is where theses fall apart.

Layer 4: Methods

Interviews. Questionnaires. Observation. Experiments.

Methods are the layer most students focus on first.

That's the wrong order.

The mistakes I see in 80% of theses.

Mistake 1. Choosing philosophy based on supervisor preference, not the research question. "My supervisor uses surveys so I use surveys." That's a method. Not a reason.

Mistake 2. Mixing incompatible philosophy and methods. An interpretivist question answered with a 400-person survey. The numbers feel safe but don't answer what the study asked.

Mistake 3. No philosophical justification in the methodology chapter. "It's common in this field" is not a justification. It is a habit dressed as reasoning.

The question every examiner asks is this:

Why these choices and not others?

Ground your answer in your research question. You will pass.

I've turned the full framework into a downloadable PDF, with a decision tree and worked examples for each philosophy. Link in the pinned comment.

Which research philosophy does your study follow? Drop your topic below and I'll suggest the best fit.

Save this. You'll need it when your methodology chapter gets difficult.

Repost to help a PhD student who's stuck on their research design. #PhDResearch #ResearchMethods

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I turn 45 today. I moved to the UK at 17 with one suitcase and no English-speaking friends. Here are 10 things I wish someone had told me at each stage of the journey.

At 17, I left Greece to study in a country where I barely understood the lectures. 
I sat in the back row and wrote down words I didn't know. 
The list was longer than my notes. 

Lesson one: discomfort is not a sign you're in the wrong place. It's a sign you're growing.

At 20, I graduated in Linguistics. At 21, I finished a Masters with distinction and registered for a PhD in Computer Engineering. 
People thought the jump was reckless. 

Lesson two: your path doesn't need to make sense to anyone but you.

At 22, I won a prestigious PhD scholarship. 
It felt like validation. But the imposter syndrome didn't leave. 

Lesson three: external recognition never fixes internal doubt.

At 23, I started working as a research assistant while completing my PhD. 
I was exhausted. I nearly quit twice. 

Lesson four: the people who finish are not the smartest. They're the ones who kept showing up.

At 25, I graduated my PhD and became an Assistant Professor. 
I thought I'd arrived. I hadn't even started. 

Lesson five: every finish line is someone else's starting block.

At 32, I became an Associate Professor. 
It took 7 years of rejected papers and failed grants. 

Lesson six: the years between promotions teach you more than the promotions themselves.

At 39, I started leading an international research institute. 

Lesson seven: academia prepares you to think. It doesn't prepare you to lead. Learn that separately.

At 40, I became a full Professor. 
Lesson eight: fulfilment comes from the work, not the title.

At 42, I started sharing on LinkedIn with 1,650 followers. 
Most colleagues thought it was a waste of time. 

Lesson nine: the best time to start building something new is when nobody is watching.

Today at 45: 20+ PhD students graduated, 40+ mentored and supervised, £10 million in research funding, 135+ publications, 228,000 people in this community.

Lesson ten: no career is a straight line. 
Mine started with a suitcase and a language I could barely speak. 
If you're at the beginning and it feels impossible, you're exactly where I was.

Keep going.

What's the one lesson your career has taught you so far? 

I'd love to hear it.

Repost if this is relatable.

#AcademicLife #PhDJourney

I lost a great PhD student because I focused on the research and not enough on the person.

Most PhD supervisors were never trained to supervise. 

No certification. 
No accountability.
No pastoral training.

We're appointed for our research. 
Not our ability to support a human being through one of the hardest experiences of their life.

I was one of them.

I now ask "how are YOU doing?" before "how is the research going?"

One question. Different supervision entirely.

What's the one thing a great supervisor does that most supervisors don't?

Repost if this rings true. 

#PhDSupervision #AcademicLife

Reviewers tore apart my thematic analysis during my PhD. "No methodological rigour." Three words that crushed me. Here is how that feedback saved my career.

I had spent 6 months doing interviews. Hours of transcribing. Weeks of reading and re-reading transcripts.

And it was all unusable.

My mistake? I thought qualitative research was just reading transcripts and highlighting interesting quotes.

I had no system. No framework. No structure.

I was coding randomly. Picking themes that "felt right." Ignoring data that didn't fit my assumptions.

The reviewers saw right through it.

That rejection forced me to start over. And starting over led me to Braun and Clarke's thematic analysis framework.

It changed everything.

Here are the 6 phases that saved my qualitative research:

Phase 1: Familiarisation
Read your data. Then read it again. And again. Take notes. Let the data speak before you start labelling anything.

Phase 2: Generating initial codes
Go through every transcript line by line. Code small. Code everything interesting. Don't try to find themes yet.

Phase 3: Searching for themes
Group your codes into potential themes. Look for patterns. Some codes will cluster naturally. Others won't fit anywhere. That's okay.

Phase 4: Reviewing themes
Check if your themes actually work. Do they hold up against the data? Some themes will merge. Others will fall apart. Be honest with yourself here.

Phase 5: Defining and naming themes
Each theme needs a clear story. What does it capture? Why does it matter? If you can't explain it in one sentence, it's not refined enough.

Phase 6: Writing up
Weave your themes into a clear narrative. Use data extracts as evidence. Connect your findings back to your research questions.

One thing I wish I knew earlier.

There are two main approaches. 
Reflexive thematic analysis lets themes emerge from the data. 
Codebook thematic analysis uses a pre-defined framework to guide coding.

Most researchers mix them up. Or worse, they don't declare which one they're using.

Reviewers notice.

The biggest mistakes I see in thematic analysis:

Treating it as a simple summary of what people said. 
Jumping to themes before properly coding. 
Not being transparent about your own biases. 
Using thematic analysis because it seems "easy" without understanding its depth.

After I rebuilt my analysis using Braun and Clarke's 6 phases, the same reviewers who rejected me praised the rigour of my work.

The framework didn't just fix my paper. It transformed how I approach all qualitative research.

Are you using thematic analysis in your research? What phase do you find most challenging?

#ThematicAnalysis #QualitativeResearch

How to build a complete conference or defense presentation slide deck in 12 minutes. A student showed me.

After supervising 25+ PhDs to completion, I thought I knew every workflow hack. 

Last week, a student 3 weeks from defense proved me wrong.

Zero slides. Full panic. 12 minutes later? A complete defense deck structure.

I felt stupid for not knowing this sooner.

For years, I lost 3 hours every time I turned research notes into slides.

My thinking was clear. My ideas were ready. But the reformatting? Painful.

Copy from notes. Paste into PowerPoint. Rebuild the structure. Realize my thinking evolved. Start again.

I thought this was just part of academic life.

I was wrong.

Here's what she showed me:

She opened Claude. Connected Gamma (took 2 minutes). Pasted her chapter summaries. Asked Claude to help structure the narrative arc.

Then, without leaving Claude, she generated the presentation layout.

12 minutes later: 15-slide defense deck. Ready to refine.

Not AI-written content. Her research. Her findings. Her voice.

Just... structured. Designed. Ready to polish.

My exact words: "Why did nobody tell me about this earlier?"

The old workflow:

→ Think in one tool
→ Copy to another
→ Rebuild the structure
→ Realize thinking evolved
→ Start again

Hours lost. Momentum killed.

The new workflow:

→ Plan in Claude
→ Generate structure & design in Gamma (inside Claude)
→ Refine both together
→ Thinking evolves. Deck evolves with it.

This isn't about AI writing your content.

It's about AI handling the mechanical design work so you can focus on your research.

I've put together 50+ prompts specifically for academic presentations.

Conference talks. Poster layouts. Defense structures. Teaching materials.

What's your most time-consuming presentation task right now?

I've put together 50+ prompts specifically for academic presentations.
Conference talks. Poster layouts. Defense structures. Teaching materials.

Repost ♻️ and comment 'FLOW' to get the complete guide within 72 hours.

Save this for the next time you need to build a deck from scratch 🔖

Gamma

#PhDLife #AcademicTwitter

Journals rejected my null findings 7 times. Then I published them myself. And they got more attention than my positive results ever did. Here's what happened:

I ran a study that showed no significant effect.

The result was important. It challenged a common assumption in my field.

But journals didn't want it.

"Not novel enough."
"Lacks sufficient impact."
"Consider a different outlet."

Seven rejections over two years.

Meanwhile I watched flashy positive results get fast tracked. 

Even when the methods were weaker than mine.

This is the publication bias problem.

Important findings get buried because they don't fit what journals want. 

Entire research directions get skewed because null results never see daylight.

I had already been using AllSci Corp. to map literature and explore related hypotheses.

Then I realized something.

If journals weren’t going to publish my null findings, I could share them directly on the same platform I was already using for discovery.

AllSci is a free platform that lets you publish your ideas without waiting for journal approval.

Here's how it works in 4 steps:

Step 1: Create your hypothesis
→ Write your hypothesis at any stage of investigation
→ No formatting requirements or submission fees

Step 2: Connect to the literature
→ AI automatically links your idea to 12 million related hypotheses
→ See supporting and refuting evidence from existing research

Step 3: Get discovered
→ Your work becomes visible to the global research community
→ Other researchers find your ideas through semantic search

Step 4: Earn credit
→ Establish authorship for early conceptual contributions
→ Build recognition even before formal publication

My null findings paper sparked conversations I never expected.

Other researchers reached out saying they had similar results. 

We connected. We collaborated. We built something bigger.

All because one platform decided truth matters more than hype.

Publication bias won't fix itself. 

But we can stop feeding it.

What null findings have you buried because journals wouldn't publish them?

Try AllSci free: www.allsci.com

#OpenScience #AcademicPublishing

AllSci Corp.

The night she almost quit her PhD, one question changed everything.
She sent me a message at 11pm. "I'm done. I can't do this anymore."

I almost missed the message. This PhD Planner changed everything.

She was 18 months into her PhD. Working full-time. Raising a family. Her supervisor had gone silent for 6 weeks. Her data analysis was a mess. She had no plan. No structure. No hope.
 
When we spoke the next morning, she told me she had already drafted the withdrawal email. She was going to send it that Friday.
 
I didn't tell her to push through.
I didn't give her a motivational speech.
I asked her one question: 

"What does your next 6 months look like, step by step?"
 
She couldn't answer. Nobody had ever asked her that.
 
So we built it together. We broke her entire PhD into fortnightly checkpoints. Each one had a single, clear deliverable. 
 
The first two weeks were rough. 
She almost cancelled twice. 
But she hit her checkpoint. 
Then the next one. 
Then the next.
 
Within 6 weeks, she had a working structure for the first time.
 
She stopped feeling lost and started feeling in control.

The method was simple:
Stage 1: Map every remaining milestone with a target date.
Stage 2: Break each one into a single deliverable every two weeks.

Not "work on chapter 3."
Instead: "Submit 2,000 words of my methodology rationale by March 14."
 
She submitted her thesis 3 months ahead of schedule. 
She passed with minor corrections. She now has 3 publications.
 
Today she's Dr Helen.
 
Here's what I've learned from experiences like hers:
 
Most PhD dropouts are not caused by lack of ability.
They're caused by lack of structure.
 
1 in 3 PhD students consider quitting in year one. 
Not because the research is too hard. 
Because nobody shows them how to plan the journey.
 
If you're in that dark place right now, you're not broken. 
You're unsupported.
 
And that can be fixed.
 
If you're in that dark place where quitting feels logical, what would make you stay?

Save for when you need it.

Repost to help a PhD student who might need this today.

#PhDLife #AcademicMentoring

--- 
I've put together the exact milestone planning template I used with this student: blank templates, worked examples for PhD and DBA, and a fortnightly checkpoint log. Free download → link in my newsletter.

After mentoring working professionals through PhDs and DBAs for over a decade, I can tell you: most choose the wrong one.
Universities won't tell you this. Both programmes pay the same fees annually.

Here's what they should tell you before you sign up.

An MBA teaches you to apply existing frameworks. 
- You learn strategy, finance, marketing, operations. 
- You graduate with a toolkit built by other people. 
- It's broad. It's fast.

It's designed to move you up inside existing structures.

A DBA teaches you to create new knowledge. 
- You identify a real problem in your industry. 
- You design original research to solve it. 
- You graduate having contributed something that didn't exist before. 
- It's deep. It's slow. It's designed to make you a thought leader.

Completely different outcomes. Same price tag.

Choose an MBA if you want to climb the corporate ladder faster, build a wide professional network, and apply proven models to your organisation.

Choose a DBA if you want to solve a specific industry problem with rigorous research, contribute original knowledge to your field, or transition into academia or senior consulting.

The time commitment is different too. 

An MBA is typically 1 to 2 years. 
A DBA is 3 to 5 years of intensive research alongside your career. 

Nobody warns you about that gap.

And here's what really bothers me. 
University admissions teams rarely explain this difference clearly. 
Why would they? 

Both programmes generate the same revenue annually. 
Whether you finish or not.

I've watched executives invest 3 years into a DBA when an MBA would have got them promoted in 12 months. 

I've watched others complete an MBA and realise they wanted to create knowledge, not just consume it.

The wrong choice doesn't just cost money. 
It costs years you cannot get back.

MBA or DBA: which path are you considering and why? 

I'll give you an honest answer below.

Save it and repost to help a colleague deciding.

#DBA #PhD

graphical user interface, text, application

I thought I knew every major finding in my field. Then an AI found research I'd missed after 15 years in minutes. Here's what happened.

I've been researching design for health and wellbeing for over two decades. I've published 130+ papers in the field. 
I thought I knew the landscape.

Well, that was until a colleague of mine recomend to check out Patsnap Eureka R&D, a free AI search engine built for R&D that covers 200 million patents and 210 million scientific papers.

I started by asking it to map how my field has evolved over 20 years. 
It identified sub-fields and saturation points I hadn't spotted. 

The results pulled from both patents and academic papers in a single search. Things I would have needed weeks to piece together manually.

Then I described a real engineering challenge I'm working on. 
It generated solution directions from consumer electronics and automotive patents. 
Work from industries I'd never have thought to search using Google Scholar.

Finally, I checked my current research for novelty. 
It surfaced patents that don't appear in Scopus or any academic database I use.

The biggest surprise was the cross-field discovery. 
Patents are organised by technical function, not academic discipline. 
An engineer at a company like Bosch might have solved your problem in 2019 using completely different terminology. 
Traditional searches miss it because the words don't match. Semantic search catches it because the meaning does.

What stood out to me: every result links back to its original source. 
Three separate modes match different stages of research. And it's free to use.

What's worth knowing: it's strongest for STEM and applied sciences. 
The three modes take some learning. 
And like any AI tool, results still need your own critical judgement.

If I missed relevant work after 15 years in my own field, there's a good chance you're missing it too.

Try it yourself. Link in comments.

Patsnap Eureka

Have you ever searched the patent literature for your research topic? 
What did you find? 

🔖 Save this for your next literature review. 
♻️ Repost to help a researcher who needs to hear this.

taplio

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