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Other ORP type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other ORP type . 2026
License: CC BY
Data sources: Datacite
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WORKSHOP: Generative AI Essentials for Life Sciences

Authors: Huynh, Minh; Smail, Rose; Fisk, Angus; Goudey, Benjamin;

WORKSHOP: Generative AI Essentials for Life Sciences

Abstract

This record includes training materials associated with the Australian BioCommons workshop 'Generative AI Essentials for Life Sciences'. This workshop took place on 1 July 2026. Workshop Description As generative AI becomes an increasingly present tool in the research landscape, using it responsibly and effectively is a critical skill. This interactive workshop is designed for life science researchers who are new to generative AI or looking to enhance their approach. You will learn to distinguish between commonly used generative AI models and align them to specific research tasks, discuss ethical risks and institutional policy obligations, and address data security and privacy considerations for research data. You will also get hands-on practice writing and refining system prompts tailored to your research area. What to bring If you have access to a generative AI tool such as Microsoft Copilot, ChatGPT, Gemini, or Claude, we recommend having it open during the session as we will be building prompts together. The workshop is designed so that everyone can participate, with or without access to a tool. Learning outcomes By the end of the workshop you should be able to: Differentiate between major generative AI models and their suitability for specific research tasks. Identify ethical risks, potential biases, and core institutional policy requirements. Identify the security of data storage and privacy implications for different research data types. Construct and refine an effective system prompt for your research domain. Lead trainers: Dr Minh Huynh, AI in Research Training Lead, Australian BioCommons and Sydney Informatics Hub, University of Sydney; Dr Rose Smail, Data Science Trainer, Sydney Informatics Hub, University of Sydney; Dr Angus Fisk, Data Science Trainer, Sydney Informatics Hub, University of Sydney; Facilitator: Dr Benjamin Goudey, AI Technical Lead, Australian BioCommons, University of Melbourne. Host: Melissa Burke, Australian BioCommons Training materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Generative AI Essentials for Life Sciences Zenodo - Event metadata.pdf: Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Generative AI Essentials for Life Sciences Workshop.pdf: slides presented during the workshop. Generative AI Essentials for Life Sciences Workshop - Padlet template.jpeg: an image of the Padlet template used for the prompting exercises Files and materials shared elsewhere: Recording of the presentation on the Australian BioCommons YouTube channel: https://youtu.be/2H0JEg-HeWo These materials were codeveloped by Australian BioCommons and the Sydney Informatics Hub.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average