Free guides
Practical answers to the questions researchers actually ask.
Short, specific guides on PhD applications, literature reviews, writing and publishing, and running experiments — each with a free template to go with it.
Foundations
3 min read
How to Email a Potential PhD Supervisor (With Templates)
Most cold emails to supervisors are ignored. Here is how to research, write, and send one that gets a reply, with a short template you can adapt.
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How to Write a PhD Statement of Purpose
A statement of purpose is a research narrative, not an autobiography. Here is a five-part structure, what to put in each part, and the mistakes that get applications ignored.
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Literature & Proposals
4 min read
How to Find a Research Gap (and Know It Is Real)
Where to look for gaps in the literature, the different kinds of gap, and how to check that yours is genuine and worth a thesis, before you spend a year on it.
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The PRISMA 2020 Flow Diagram, Step by Step
What each box of the PRISMA 2020 flow diagram means, how to count records at every stage, and the arithmetic checks that catch mistakes before a reviewer does.
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Writing & Publishing
3 min read
How to Write a Response to Reviewers (Journal Revisions)
A revision decision is not a rejection. Learn how to structure a point-by-point response letter that answers every comment, disagrees politely, and makes the editor's job easy.
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How to Write a NeurIPS / ICML Rebuttal That Actually Changes Scores
Conference rebuttals are short, rushed, and read by tired people. Here is how to prioritise, what evidence to include, and the mistakes that waste your limited space.
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How to Spot a Predatory Journal Before You Submit
A practical checklist for judging whether a journal is legitimate: the warning signs, the independent checks to run, and why no single list can do the work for you.
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How to Prepare for a PhD Viva (Thesis Defence)
What examiners are really looking for, a week-by-week preparation plan, the questions to rehearse, and how to handle the ones you cannot answer.
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Technical & AI Tools
3 min read
t-test vs Bootstrap: How to Choose a Significance Test for ML Results
Which statistical test fits which machine-learning comparison: two models on one test set, several seeds, or many datasets. Includes a working paired-bootstrap example.
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SLURM Job Script Examples for PyTorch (Single GPU, Arrays, Multi-GPU)
Three working SLURM job scripts for ML research: one GPU, a job array across seeds, and multi-GPU with torchrun, plus the mistakes that waste the most time.
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