Course overview
Start hereAI for Postdoctoral Researchers
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Daniela's Wednesday, two ways

9 lessons · 26 prompts

A day in the life of a Postdoctoral Researcher: what changes with these prompts.

Track progress as a member

Daniela, a postdoctoral researcher in materials science.

Daniela starts Wednesday with forty PDFs on perovskite stability and a grant deadline in three weeks. She opens ChatGPT and uses the literature review prompt: summarize each paper in five lines, group them by theme, and list the gaps. By nine she has a clear map of the field and two ideas for her next experiment.

At ten she switches to Claude for the manuscript prompt. Her discussion section is a pile of rough notes about grain boundary passivation. She asks the AI to turn the notes into three paragraphs with a calm academic tone, then edits the result herself. By lunch the section is ready for her PI.

Afternoon is data. Her Python code for XRD peak fitting keeps failing on a messy batch. She uses the data analysis prompt in Gemini to find the bug and clean the outliers. Then she uses the lab admin prompt to draft a progress report email, which takes ten minutes instead of an hour.

Daniela leaves at five thirty. She walks her dog, cooks a real dinner, and reads a novel. The papers are sorted, the draft is moving, and the grant outline is started. The time she won back is hers.

Before

  • Tabs open until midnight
  • Papers read in a blur
  • Reviewer comments feel personal
  • Weekends lost to email

After this course

  • Papers sorted by Friday lunch
  • Draft sections before noon
  • Clear answers for reviewers
  • Home by six most days

What you'll learn

  • Literature reviews: Turn a folder of PDFs into a clear summary of themes and gaps.
  • Manuscript drafting: Shape rough notes into polished sections and answer reviewer comments.
  • Grant writing: Structure proposals and justify budgets with clear language.
  • Experiment design: Plan robust experiments and troubleshoot when things fail.
  • Data analysis: Write and debug analysis code, interpret stats, and clean messy data.
  • Conference talks: Prepare talk scripts, posters, and practice Q&A.
  • Mentoring students: Give better feedback and build training plans.
  • Lab admin: Handle emails, progress reports, and peer review drafts.

How this course works

  1. 9 lessonsOne task of your job each, from literature review & summaries to peer review & research ethics.
  2. Ready-to-paste promptsCopy, fill in the parts in {{brackets}}, paste into ChatGPT, Claude or Gemini.
  3. Tick and completeTick the prompts you tried and mark each lesson complete.
  4. Get certifiedFinish and keep the prompts as your own library.