Angela Priest

I'm a data geek and process nerd who loves to build people up and help them grow. For 20 years, I've been turning chaos into order at companies across all stages of growth to ensure that their teams flourish. I'm now throwing my passion for helping people into helping PhDs, PostDocs, and Mid-Career Researchers get jobs in industry. My goal is simple: to help brilliant minds thrive outside the academic world and make real impact in their new careers.

Check out my website to learn more: www.alma.me

Co-Founder and COO

At Alma.Me, we help PhDs kick start their careers in industry through on-demand courses, online communities, networking, and resources to help them make the transition from academia to industry with confidence.

🩺I take researchers from goals to published results 🇮🇳 🇬🇧 Founder II Academic Writing Mentor || AI researcher || Homeopath ✅️Need Research Solutions❓️ Go to my ABOUT section.🔻

I specialize in testing AI tools for literature reviews, academic writing, editing and statistical analysis, sharing insights that enhance research productivity and workflow.

As a PhD in Life Sciences, I am passionate about guiding academics and PhDs from research concept to completion, ensuring they have the right tools, methodologies and mentorship to succeed.

🎯 How I Help Researchers & PhDs??

Through 

🟪 RESEARCH MADE CLEAR 🟪

I offer consultancy services in:

✅ Scientific Writing & Editing: Ensuring clarity, coherence and impact in research papers.
✅ PhD Mentorship & Research Methodology: Supporting scholars in thesis writing, research design, and proposal development.
✅ Data & Statistical Analysis: Providing expertise in biostatistics, data analysis and result interpretation.
✅ Faculty & Student Development: Training in AI-powered research tools & ethical considerations.
✅️ Webinars & Workshops: How to use AI tools for Literature Review, research writing and Research Management, ethically.

🔍 My Experience & Research Contributions:

With 10+ years of experience across multidisciplinary research projects, I have:
📌 Led & coordinated multiple research trials and longitudinal surveys as a Research Manager.
📌 Published 8+ peer-reviewed papers in evidence-based medical writing.
📌 Developed the MAPNI questionnaire—a validated tool assessing perceived stigma towards mental illness in India.
📌 Taught Research Methodology & Biostatistics as an 'Assistant Professor', mentoring 500+ academic professionals in thesis & dissertation writing.
📌 Supervised successful scholarship applications for the Short-Term Studentship in Homoeopathy (STSH, CCRH, India).

📢 Let’s Connect
✅️Need expert guidance in research writing, AI tools or statistical analysis?
✅️Looking for collaborations, training sessions or mentorship?

💌 Email: dps@researchmadeclear.com
📩 DM me here on LinkedIn!

Dr Priya Singh PhD💜MD (Hom.)

More research is needed’ is not a research gap

Saying “there isn’t much research” is not enough. 
Reviewers want to know exactly what is missing and there are different kinds of gaps.

Here are some of the most important ones researchers should recognize:
 🔹 Evidence gap – We simply don’t have enough solid data yet.
 🔹 Knowledge gap – We don’t fully understand why or how something works.
 🔹 Practical gap – Research exists, but it’s not being used in real settings.
 🔹 Population gap – Certain groups are left out of studies.
 🔹 Methodological gap – The tools or methods used so far are weak or outdated.
 🔹 Theoretical gap – No strong theory explains the issue clearly.
 🔹 Geographical gap – Research is focused on some regions and ignores others.
 🔹 Empirical gap – Important variables haven’t been studied together.
 
When you name the type of gap, your study stops sounding general and starts sounding necessary.

If you’re writing a proposal or thesis, start by asking:
 What kind of gap am I actually filling?

PS: What would you add here?
Share in the comments

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Subscribe to my YT channel: https://lnkd.in/eSBGiCz8 for Tutorials and tips

Dr Priya Singh PhD💜MD(Hom.)

Helping PhDs & researchers complete and publish high-quality research PhD mentor || Thesis reviewer || Academic writing expert Training research professionals in working with AI

Before your next submission, read this 👇 

If you’re trying to publish in a good journal and feeling stuck, this paper is genuinely worth your time

It walks you step by step through what actually makes a paper publishable — in plain, practical terms.

Instead of vague advice, it explains:
✅ What editors and reviewers look for in a strong paper
✅ Why many solid studies still get rejected
✅ How to write each section — title, abstract, introduction, methods, findings, discussion, and conclusions — in a way that strengthens your chances of acceptance
✅ Common mistakes that quietly kill good manuscripts

What makes it especially helpful is that it focuses on presentation, structure, and clarity.

If you’re:
🔹 revising a manuscript
🔹 preparing your first journal article
🔹 mentoring students on academic writing
…this paper works like a behind-the-scenes guide to the review process.

Definitely one to read with your own draft open beside you. You’ll start spotting exactly where your paper can be sharper and more convincing.

PS: If you could get expert help on just one section of your paper, which would it be?

Share in the comments

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Follow for more research writing insights.

HOW TO WRITE REALLY GOOD ARTICLES 

Publishing in Q1 or high-impact journals is not about luck 😯 

This editorial makes one thing very clear 

most papers are rejected not because the research is weak, but because it sends the wrong signals.

✅ Lack of originality.
✅ Unclear contribution.
✅ Narrow topics.
✅ Flawed design.
✅ Poor writing flow.
✅ Out-of-scope submissions.

These are not small issues. They are instant filters.

What I appreciated most is how practical the message is:
 
1. Editors look for generalisable insight, not local descriptions  
2. Theory and contribution matter, even in applied work
3. Methodological rigour is expected, not optional
4. Writing quality is part of scholarly quality

If you are submitting repeatedly and getting desk-rejected, this editorial is worth reading slowly and strategically.

PS: What was the hardest publishing lesson you had to learn the slow way?
Share in the comments

REPOST to help others publish better.

Follow for more tips on publishing 

-----------------------------------------------------------------------------------------------

I’m Dr Priya Singh Founder, Research Made Clear 
I offer review, academic editing, and proofreading to help improve quality of your resaerch papers and thesis before submission. DM if you’d like support.

Publishing in Premier & Q1 Journals

If your qualitative paper ends at themes, you may be stopping too early.

Rigor in qualitative research is not just about coding neatly or reporting themes clearly. 

It is about thinking conceptually and being intentional about how findings are elevated into a model that others can use, test, and build on.

Process transparency matters most.

When readers can see how you moved from raw data to ideas, your work becomes easier to trust, teach, and replicate across disciplines and methods.

If you struggle with the question
 “I have good themes… now what?”
 this paper is worth your time 👇 

PS: Is your qualitative paper descriptive or conceptual?
Share in the comments

REPOST to help others.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Hi I am Dr Priya, Founder Research Made Clear

I help researchers turn qualitative analysis into publishable papers. Need help? 

Feel free to DM.

Step by Step Process of Thematic Analysis in Qual Research

No one teaches you the real rules of publishing ❌ 

PhDs are trained to collect data, run analyses and read theory

But the rules that actually decide accept or reject?

Those are rarely taught.

Academic publishing operates on a set of tacit rules about contribution, writing, positioning, and reviewer expectations that many supervisors assume you already know.

PhDs struggle because they were never shown how the game is really played.

PS: Which of these hidden rules did no one tell you early in your research journey?

Share in the comments

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100 RESEARCH RULES OF THE GAME

A strong conclusion doesn’t close the paper. It opens the conversation.

Your conclusion is not a summary.
It’s your final chance to shape how the reader remembers your work.

I suggest my mentees to follow these for writing a strong conclusion 👇

1. Start by answering the research question clearly.

Say it plainly.
What did you find overall?
If someone only reads your conclusion, they should still understand the main takeaway.

2. Zoom out before you close

Move from specifics to the bigger picture.
Explain what your findings mean for the field, practice, policy, or future research.
This shows maturity, not exaggeration.

3. Link back to the problem you started with

A good conclusion feels like a full circle.
Remind the reader why the problem mattered in the first place and how your study helped address it.

4. Acknowledge limitations calmly

One or two sentences are enough.
State them factually, without apologising or weakening your work.
Confidence comes from transparency.

5. End with forward direction, not repetition

Don’t restate results again.
Instead, point forward:
 – What should happen next?
 – What questions remain open?
 – What could others build on?
That’s how research stays alive beyond the paper.

Save this if you’re writing a paper, thesis, or dissertation.

PS: What do you personally struggle with most when writing conclusions?
Share in the comments.

REPOST to help others.

Follow Dr Priya SIngh for more research writing guides Research Made Clear

Getting a paper published isn’t about “luck”
It’s about fit, clarity, and discipline.

This checklist from SAGE Publishing quietly reminds us of what many early researchers miss:

✅A good paper answers a real question, not just a gap for the sake of a gap
✅Journals care deeply about scope, structure, and audience
✅Small things (word limits, references, blind review rules) matter more than we think
✅Editors want clarity, not cleverness
✅And publication is as much about preparation as it is about results

Strong research fails every day because it wasn’t positioned well.

Before submitting, ask yourself: Does this journal want the paper I’ve written or am I hoping they will?

PS: What’s one lesson about publishing you learned the hard way?
Share in the comments

REPOST to help others

Goldmines for learning how real PhDs are written 👇 

High-quality, free PhD thesis repositories worth bookmarking:
1. 1. Global & Multi-Institution Aggregators
✅ Open Access Theses and Dissertations (OATD)
🔗 https://oatd.org
✅ The Networked Digital Library of Theses and Dissertations (NDLTD)
🔗 http://www.ndltd.org
✅ EBSCO Open Dissertations
🔗 https://lnkd.in/eCiUEiGb
✅ EThOS (British Library)
UK doctoral theses with many full-text downloads.
🔗 https://ethos.bl.uk
✅ Thesis Commons
A community-driven open repository for author-deposited theses and dissertations.
🔗 https://thesiscommons.org/

2. National / Regional or Subject-Specific Repositories
✅ Shodhganga (India)
Large open repository of Indian PhD theses.
🔗 https://lnkd.in/eRqD6Qsk
✅ Swedish University Dissertations (dissertations.se)
Index of dissertations in English from Swedish universities, many with PDFs.
🔗 https://lnkd.in/eHTSr9Cn
✅ theses.fr (France)
Access point to French doctoral theses across French institutions.
🔗 https://www.theses.fr/

3. Institutional Open Repositories 
✅ MIT DSpace
Theses and dissertations from MIT.
🔗 https://dspace.mit.edu
✅ Harvard DASH
Harvard University open access repository.
🔗 https://dash.harvard.edu
✅ Cambridge Apollo
University of Cambridge open repository.
🔗 https://lnkd.in/e86rnQn2
✅ SUNScholar (Stellenbosch University)
South African university theses.
🔗 https://scholar.sun.ac.za
✅ OhioLINK ETD Center
Consortium repository for theses from participating Ohio universities.
🔗 https://etd.ohiolink.edu/
✅ eScholarship (University of California)
Open access repository including UC theses/dissertations.
🔗 https://escholarship.org/

4. Tools & Directories that Aid Thesis Discovery
✅ BASE (Bielefeld Academic Search Engine)
Indexes open access content from repositories worldwide (theses included).
🔗 https://lnkd.in/eWbpj-hv
✅ WorldCat (free advanced search)
Global library catalogue where you can filter for theses/dissertations.
🔗 https://www.worldcat.org
✅ OpenDOAR / ROAR
Directories of open access institutional repositories (many contain theses).
🔗 https://lnkd.in/eDvBvcAm

Here is how PhD scholars can benefit from open thesis repositories:
• See how strong research questions are framed
 • Understand chapter structures that actually passed examination
 • Learn how methods and limitations are written in practice
 • See discipline-specific writing styles, not generic templates
 • Identify gaps and angles that published papers often hide
 • Reduce anxiety by realising: your draft doesn’t have to be perfect to be valid

PhDs are not written by magic. They are written by patterns you can learn.

PS: Which thesis repositories have helped you most during your PhD journey?

Share in the comments.

REPOST to help others

What do you check first in a paper?

Papers with clear charts and diagrams get read more, understood faster, and remembered longer.

Why?
Because reviewers and readers don’t read line by line.

They scan.

Figures act as cognitive anchors:
 ✅ They summarise complex arguments at a glance
 ✅ They guide the reader through results
 ✅ They signal clarity, rigour, and confidence
 ✅ They reduce mental effort for busy reviewers

A strong figure can do what three paragraphs struggle to explain.

That’s why well-designed diagrams often get cited, reused in talks, and remembered while text-heavy papers get skimmed and forgotten.

This doesn’t mean “add more charts.”

 It means add purposeful visuals that carry the argument forward.

If your key finding cannot be visualised clearly, it is often not clear enough yet.

📌 Tools for data visualisation (charts, graphs, dashboards)
Tableau – Interactive dashboards; widely used in research and policy settings
Microsoft Power BI – Strong for structured data and reporting
GraphPad Prism – A staple in biomedical and experimental research
R (ggplot2) – Publication-quality figures with full analytical control
Python (Matplotlib / Seaborn) – Flexible, reproducible scientific visualisation

📌 Tools for scientific illustrations & diagrams (conceptual figures, workflows)
BioRender – Gold standard for life-science figures
Mind the Graph – Accessible visuals for papers and presentations
Adobe Illustrator – High-end, journal-ready figure design
Inkscape – Free alternative for scalable diagrams
PowerPoint – Still one of the most used tools for assembling publication figures

PS: What more tools would you add?
Share in the comments

Repost to help others.

Follow Dr Priya Singh, Founder Research Made Clear for morte academic writing tips.

If your research gap is weak, your whole study stands on shaky ground.

Finding a real research gap is about seeing what is missing, unclear, or unresolved in what we already know.

Here are some Do’s and Don’ts to help you get it right 👇
✅ DO’s When Identifying a Research Gap

1. Do read for patterns, not just papers

Don’t treat articles like isolated pieces. 
Look for:
✅Repeated limitations
✅Conflicting findings
✅“Future research should…” statements
 Patterns point to gaps.

2. Do map what is known vs. unknown
Make two columns:
✅What researchers agree on
❓What is still unclear, under-tested, or debated
 Gaps live in the second column.

3. Do narrow the context
A gap becomes strong when it is specific:
✅A certain population
✅A setting or country
✅A method not yet used
✅A variable not yet examined together with others
Broad gaps are weak. Focused gaps are publishable.

4. Do check recency
A gap from 2012 may already be filled. Always check the latest 3–5 years of literature before finalizing your gap.

5. Do connect the gap to a real problem
Editors and reviewers love gaps that matter.
 
Ask: Who is affected if this gap remains unaddressed?

❌ DON’Ts That Weaken Your Research Gap

1. Instead of “No one has studied this”
 This is rarely true and reviewers will prove it in seconds.
 Instead say:
 👉 “Limited research has examined…”
 👉 “Findings remain inconsistent regarding…”

2. Don’t confuse a topic with a gap
“Social media and mental health” is a topic.
 
A gap sounds like:
“Few longitudinal studies have examined how social media use predicts anxiety among adolescents in low-income settings.”

3. Don’t copy the ‘future research’ line blindly
Use it as a clue, not as your gap. You still need to justify why that missing piece is important.

4. Don’t make the gap too big
You are not solving the entire field’s problem in one PhD.
A good gap is manageable, specific, and researchable.

5. Don’t write the gap before the review is mature
If you decide your gap too early, you’ll force the literature to fit your idea instead of letting the evidence guide you.

PS: Are you studying a topic… or solving a clearly defined gap?
Share in the comments

REPOST to help others.

PowerPoint feels clumsy and time-consuming

That is where graphical abstracts come in.

A graphical abstract is a single visual snapshot of your study:
the question, the method, and the key takeaway, all at a glance.

Why do Graphical abstracts matter today?
·      Editors use them to quickly grasp relevance
·      Reviewers use them to understand logic and flow
·      Readers use them to decide whether to click, read, or cite
·      Journals use them to increase visibility and sharing

In short, A good graphical abstract earns your paper attention.
Yet this is where many researchers struggle.

Recently, one of my mentees asked me for a practical tool to create a graphical abstract quickly, without design stress.

That’s why, I am sharing a demo showing how I used AnswerThis (YC F25) to break a study into visual components, convert methods and findings into clean diagram.

Step 1: Go to https://lnkd.in/ea5SUYVg and open the Diagrams feature (or select Diagram from the creation options).

Step 2: Select Diagram, then tell the tool what you want to create.
In my case, I wanted a graphical abstract.

Step 3: Paste your study abstract + add a clear instruction
I copied the study’s abstract and used a prompt like this:
“Create a graphical abstract for this study. Use the abstract below to summarise the background, aim, methods, key findings, and conclusion in a clean, journal-style layout. Abstract: [paste abstract]”

Step 4: Run the prompt
Click the red up arrow / Run button to generate the diagram.

Step 5: Review what the tool generates
Within a few minutes, the tool produces a graphical abstract and typically provides:
a short overview/explanation of the visual structure
how it translated the abstract into sections (aim, methods, findings, takeaway)

Step 6: Export the graphic
The output is available as a high-quality PNG. You can:
use it directly, or
use it as a base draft and refine labels/layout in your preferred design tool.

Step 7: Accuracy check (non-negotiable)
Before using it in a submission or posting it online:
verify every label, number, direction of effect, and conclusion
ensure the visual matches the paper (not assumptions or “typical” logic)

The key point here is not the tool itself, but what AI now enables.

AnswerThis (YC F25) can help researchers:
·      translate dense text into visual logic
·      reduce cognitive load during design
·      focus on clarity, not cosmetics
·      save hours without compromising accuracy

Graphical abstracts are no longer nice to have.
 
They are part of modern scholarly communication in many fields.

PS: What tools are you using to create graphical abstracts or research visuals?
Share in the comments

REPOST to help others.

Data speaks in results. You speak in the discussion.

The discussion is where you prove you understand your results.

Here’s a simple way to write a strong discussion section 👇

1. Start with the big answer, not the details
 Open by answering your research question in plain language.
 What did you actually find?
 
2. Explain the “why,” not just the “what”
 Results tell what happened.
 Discussion explains why it matters.
 
Ask yourself:
 “Why did this result turn out this way?”
 “What does this tell us about the problem?”

3. Connect your findings to existing studies
 Don’t list papers.
 Compare ideas.

 Say whether your findings:
 – support previous work
 – challenge it
 – extend it to a new context

4. Be honest about limitations
 Every study has limits.
 
Name them calmly and briefly.
Then explain why your findings are still useful despite those limits.

5. End with implications, not repetition
 So what?
 
What should researchers, practitioners, or policymakers do differently now?
This is where your study earns its value.

Strong discussions don’t restate data.
They interpret, connect, and position it.

PS: Which part of the discussion do you find hardest to write?
Share in the comments.

REPOST to help others.

Follow Dr Priya Singh for more research writing guides 

Founder, Research Made Clear

There was a phase in my own PhD where I didn’t feel “stuck”.

I was busy.

Reading more. Tweaking things. Making notes. Starting and restarting documents.
 
Telling myself, I’m working… just not ready yet.

Weeks passed. Then months.
Nothing was technically wrong.
 
But I had quietly lost the thread.

What I see now, after mentoring so many PhDs is that this happens to almost everyone.

Because a PhD is long enough for you to forget what you’re actually trying to finish.

You stay productive, but directionless.
You mistake movement for progress.

Here’s what actually helps:

✅ Decide what is in scope and what is not. Write it down. Stop renegotiating it daily.
✅ Decide on a weekly finish line (a section, a figure, 1,500 words, not “work on Chapter 3”).
✅ Decide when something is good enough to send, not perfect enough to keep.
✅ Decide that unclear feedback means act and clarify later, not pause indefinitely.

Finish one small thing this week.
Momentum follows decisions.

That’s how PhDs get finished.

PS: What are you finishing next—section, figure, or analysis?
Share in the comments.

REPOST for every PhD who needs to know this,

Follow Dr Priya Singh, Founder Research Made Clear for PhD survival tips.

Ten simple Rules for finishing your PhD

❓Three terms. One chapter. Endless confusion 🤔 

Literature review, theoretical framework, and conceptual framework do not mean the same thing. 

And confusing them can weaken your entire study.

Here is the difference in simple terms:
1️⃣ Literature Review = What we already know
This is where you show the research landscape.

You summarize, compare, and critique previous studies to explain:
✅ What has been studied
✅ What findings exist
✅ Where the gaps are

Example:
If your topic is AI use in medical education, your literature review might discuss:
Studies on AI tools for diagnosis training
Research on student attitudes toward AI
Evidence on learning outcomes

2️⃣ Theoretical Framework = The theory you stand on
This is about existing theory that explains why things happen.

✅ You choose a well-established theory that helps interpret your study.

Example:
If you use Technology Acceptance Model (TAM), you might say:
Students’ perceived usefulness of AI influences their intention to use it
Perceived ease of use affects adoption

Here, the theory provides a lens. You are saying:
 “I am viewing my study through this theory.”

3️⃣ Conceptual Framework = Your study’s blueprint
This is your model, built for your specific research question.
 
It may be inspired by theory, but it is customized.

You show:
✅ Your key variables
✅ How you believe they are related

Example:
You may propose:
AI training → AI confidence → AI usage in clinical learning
And you may add:
Faculty support strengthens this relationship

That diagram? That’s your conceptual framework.

When you separate them clearly:
✅ Your literature review justifies the gap
✅ Your theoretical framework explains the logic
✅ Your conceptual framework shows your research design

PS:  Are you describing what others found… or explaining how your variables connect?

Share in the comment.

REPOST to help others.

A systematic review without a plan is just academic burnout in slow motion.

A PhD student once told me, “I thought a systematic review would take 3 months. It’s been more… and I’m still screening papers.”

That frustration is more common than people admit.

Systematic reviews and meta-analyses look straightforward from the outside. 
Search some databases, read papers, summarize results. 

But in reality, they can quietly drain months (sometimes years), and in my opinion, most delays happen because the process is not structured from the start.

A strong review involves designing the journey, before you begin walking.

Here’s what saves time, stress, and rework:
✅ Be brutally clear about your research question before you search
 A vague question = endless screening and confusion later.
✅ Decide your rules early
Inclusion, exclusion, outcomes, study types. If you define these late, you’ll keep second-guessing every paper.
✅ Work in pairs, not alone
Independent screening and extraction don’t just reduce bias. They reduce mistakes that cost weeks to fix.
✅ Treat data like a database.
If extraction isn’t structured, analysis becomes a nightmare.
✅ Don’t assume you must do a meta-analysis
Sometimes the most honest and useful review is narrative. Forcing numbers where they don’t belong weakens your study.
✅ Document as you go
Trying to rebuild your flow diagram and methods section at the end is one of the biggest time traps in evidence synthesis.

A well-planned systematic review doesn’t just produce stronger evidence.
 It protects your time, your energy, and your sanity.

PS: Did your review take much longer than you expected?
Share in the comments

REPOST to help others.

The Discussion section is where good papers either land… or lose reviewers.

A strong Discussion is not a summary.
It’s your argument.

✅ Start with the answer, not the data
Open by clearly stating what your findings mean, not what you found. The reader already knows the results.

✅ Anchor every claim to evidence
If you say something is “important” or “novel,” explain why and link it back to theory or prior studies.

✅ Compare, don’t compete
Show how your findings align with, extend, or challenge existing work. You’re joining a conversation, not trying to win it.

✅ Explain surprises honestly
 Unexpected results are not weaknesses if you interpret them thoughtfully.

✅ Separate interpretation from implication
First explain what the results mean. Then discuss why they matter for practice, policy, or future research.

✅ End with contribution, not repetition
Your final paragraph should answer one question:
What does the field know now that it didn’t know before this study?

If Results show what happened,
Discussion explains why it matters.
That distinction changes everything.

PS: What would you add?
Share in the comments.

REPOST to help others

How we write a manuscript discussion

Last year, a mentee of mine almost gave up on her PhD dream!!

She had strong grades. 
A meaningful topic. 
Real motivation.

But after multiple university rejections, she was exhausted.

What hurt most wasn’t just the “no.”
It was the time.

Months spent drafting.
Weeks waiting for decisions.
Emotional energy poured into applications that quietly went nowhere.

When we finally sat down to review her research proposal, the issue became clear very quickly:

Her idea made sense in her head.
But on paper, it didn’t yet look like a clear, doable research plan.

And that’s where many applicants struggle.

Universities aren’t only asking,
“Is this topic interesting?”

They’re asking:
Do we clearly understand the problem?
Are the questions focused enough to guide a study?
Is the method realistic for a PhD timeline?
Does this project show a logical path from idea to outcome?

Once we reworked her proposal with those questions in mind, everything changed.

Not her topic.
Not her passion.
 
Just the clarity, structure, and flow of her proposal.
In the next application round, she received interview invitations and an offer.

That experience is exactly why I created this guide on crafting a strong research proposal. 👇 

Because a proposal is a document that helps reviewers quickly see:
✅ what you want to study
✅ why it matters
✅ how you will actually do it
✅ and whether the project is feasible

A good proposal doesn’t try to sound impressive.
It makes the research easy to understand and easy to trust.

If you’re planning to apply for a PhD or research program, don’t wait for another rejection to realise the proposal might be the missing piece.

PS: What part of writing a research proposal feels hardest for you right now?
Share in the comments.

Repost to help others. 

Follow Dr Priya Singh, Founder Research Made Clear for more research tips.

A PhD is rarely finished by inspiration. It’s finished by routine.

Writing a PhD thesis is a process.

After years of supervising and examining theses, here’s the simple truth most students aren’t told:

1. Start with structure before sentences
Do not begin by writing chapters.

Begin by locking:
Your research question
Your chapter map
What each chapter must prove

If you can explain your thesis structure on one page, writing becomes execution, not confusion.

2. Write to answer questions, not to sound academic
Every section exists to answer one question:

Introduction → What problem are you solving and why now?
Literature review → What do we already know, and where is the gap?
Methods → Why was this the right way to study it?
Results → What did you find?
Discussion → What does it mean?


3. Separate “thinking” from “writing”
Most PhDs get stuck because they try to think and write at the same time.

Instead:
Think first (notes, bullet points, rough logic)
Write later (clean sentences, flow, references)
This removes perfectionism from the process.

4. Write small, consistently
You do not need long, perfect writing days.

You need:
30–45 minutes
One clear task
One subsection at a time

Consistency beats intensity every single time.

5. Expect ugly drafts
A strong thesis always starts messy.

Your first draft is not evidence of your intelligence.
It is raw material.

Clarity comes from revision, not from waiting to feel “ready.”

6. Treat feedback as data, not judgment
Supervisors are not reading to admire your work.
They are reading to stress-test it.

When feedback comes:
Categorise it (structure, clarity, theory, method)
Address patterns, not emotions
Revise strategically, not defensively

This is how strong theses are built.

PS: Are you writing regularly, or only when deadlines panic you into it?
Share in the comments.

REPOST to help others

Follow Dr Priya Singh, Founder Research Made Clear for more PhD writing tips.

The Method section is not a formality.
 It is where reviewers decide whether to trust your study.

Here’s how to use it properly when writing 👇

1. Research Design
Don’t just name the design.
 
Briefly explain why this design was the right choice for your research question.

2. Participants / Sample
Be explicit about:
Who was included (and excluded)
How participants were selected
Ethical approval and informed consent
If there are sampling limits or constraints, name them calmly. 

3. Variables / Constructs
Clarity matters more than complexity.

Quantitative: define independent, dependent, and control variables clearly
Qualitative: explain key concepts, themes, or guiding questions

If readers can’t tell what you actually studied, the analysis won’t matter.

4. Data Analysis
Explain how you made sense of the data, step by step.
What analysis approach did you use?
Why was it appropriate?
What software supported the process?

5️⃣ Limitations (Optional, but powerful)
Strong papers don’t hide limitations.
They frame them responsibly.

Briefly note:
Sample constraints
Potential biases
Limits to generalisation

Other details that reviewers quietly appreciate
Software and tools used
Study timeline
Ethics approval reference number

Small details = big trust signals.

📌 Save this infographic for your next paper.

PS: What would you add? 

Follow Dr. Priya Singh for practical research writing guidance.

Most thesis stress comes from unclear expectations‼️ 

One of the fastest ways to feel confident and finish is to understand where you are in the thesis journey and what your stage is actually trying to train you to do.

Here are few things I advice my mentees: 
✅ Ask “What does success look like for this thesis?” In your first supervision meeting, request 2–3 sample theses/dissertations your department considers “good.” 
✅ Treat your thesis like a project, not a mood. Put milestones on a calendar: proposal, ethics, data collection, analysis, chapter drafts, revisions. 
✅ Create a “decision log.” Every time you choose a method, sampling approach, exclusion rule, or framework—write a 2–3 line justification. This saves you during viva/defense and revisions.
✅ Write earlier than you feel ready. Don’t wait for “complete reading.” Start with rough chapter skeletons and expand weekly. Writing is how thinking gets clearer.
✅ Use chapter checklists. Each chapter needs a purpose, a through-line, and a final “so what.” If you can’t summarise a chapter in one sentence, it’s still fuzzy.
✅ Separate reading into two lists: “Must-cite” (core, directly relevant) and “Nice-to-know” (interesting but optional). This prevents literature-review overload.
✅ Build a weekly evidence habit. Every week produce something tangible: a table, a figure, coded notes, an analysis memo, 500–800 words. 
✅ Get alignment on feedback style. Ask your supervisor: “Do you prefer full-chapter drafts or smaller sections?” and “Should I submit polished writing or rough drafts?” 
✅ Stop comparing timelines. Different disciplines and data types move at different speeds. Compare your progress to your plan, not someone else’s chapter count.
✅ Protect your “deep work” slots. Two focused sessions a week (even 60–90 minutes) consistently beats weekend panic-writing.

PS: Where are you right now in your thesis journey and what’s the one thing you wish someone had explained earlier?

Share in the comments

REPOST to help others.

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I’m Dr Priya Singh, Founder of Research Made Clear

I support researchers with thesis review, academic editing, and proofreading to strengthen clarity, structure, and overall quality before submission—DM me if you’d like support.

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