AI for Article Writing: a Soft Toolbox

1-2 April 2026

Romain-Daniel Gosselin, Dr., DataBio

Romain-Daniel Gosselin, Dr., DataBio

This immersive two-day course aims at equipping participants with knowledge and practical skills in AI-assisted scientific writing. The program covers AI fundamentals, ethical considerations, and hands-on applications.

Participants will learn good practices as well as major caveats in prompt engineering, scientific writing, and literature retrieval using usual web-based AI tools. Through interactive workshops and problem-solving sessions, students will develop critical skills, all without requiring technical expertise in data science.

The course particularly emphasizes the responsible use of AI in research.

Provisory Program

Day 1: Foundations and practical AI applications in writing

• Introduction to AI in life sciences: Brief history of AI/ML/NLP/LLM; introduction of algorithm functioning; current landscape of available tools for life scientists.
• Ethical considerations in AI: Research integrity; potential biases; considerations about authorship and citations; data privacy and confidentiality; institutional guidelines.
• Prompt engineering fundamentals: CraNing effective prompts; zero-shot vs few-shot learning; techniques for scientific writing; avoiding and spoPng allucinations; practical exercises in prompt design.
• AI for scientific writing: Literature retrieval and summarization; draNing manuscript sections; reference management; edition and refinement techniques; hands-on writing workshop.
• Practical session: Writing.
• Use of generic (ex: ChatGPT, Claude) and specific (ex: askyourpdf, consensus) tools; comparative analysis of outputs and capabilities; Hands-on exploration.

Day 2: Advanced AI functionalities of AI in the management of scientific contents

• AI in literature retrieval: Use of generic (ex: ChatGPT, Claude) and specific (ex: askyourpdf, consensus) tools.
• PiXalls of AI use in article writing: Be wary of "hallucinations"; issues with content standardisation and tortured phases.
• Practical workshop: writing. Group challenges: writing a short (2 pages) referenced article on a given topic (free choice of tools); presentations of group outputs; critical evaluation.
• Can I peer review helped by AI? Extracting information from a manuscript; detecting the use of AI; structuring a review report; journal regulations.
• Practical workshop: peer reviewing. Group challenges: peer reviewing a given (short) text; focus on the detection of AI contents, detection of fabricated images, and the writing of the review report.
• Caveat with AI detectors: Presentation of detectors; AI detectors lack reliability; A variety of outputs.
• Final conclusions: Course wrap-up, perspectives, recommendations for continued learning

University of Lausanne, Room TBA

This course is organized in collaboration with the CUSO Doctoral Programs in Ecology & Evolution, Microbial Sciences and StarOmics and the Doctoral School in Life Sciences of Neuchâtel (DSLS)

Reimbursements for CUSO MPS Students:
Train ticket, 2°class, half-fare from your institution to the place of the activity 

Reimbursement of your travel tickets can be asked online through your MyCUSO. 
See HERE for the procedure.

REGISTRATION IS CLOSE

Deadline for registration: TBA

- 5 places for CUSO MPS
- 5 places for CUSO StarOmics
- 4 places for CUSO Microbiology
- 3 places for CUSO Ecology&Evolution
- 3 places for DSLS

For cancellations after the registration deadline or no-show: 50 CHF administrative fee

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