AI and data science summer lab

This summer lab is a free two-day event designed to equip a cohort of emerging researchers with practical AI and data science skills and encourage transdisciplinary connections.

This event is open to applicants from all New Zealand universities, public research organisations, and independent research organisations, and is sponsored by Beyond Prediction: Explanatory and Transparent Data Science, a programme funded by the MBIE Strategic Science Investment Fund (SSIF) Data Science platform.

Date: 19-20 February 2026

Location: Science Centre, University of Auckland

Cost: Free

Food will be provided, but travel, accommodation, and related expenses are the responsibility of participants. Successful applicants will receive more information closer to the event.

Thursday 19 February

• A practical workshop on 'Large Language Model workflows for data analysis in Python' with Dr Kyle Hemming, or 'Reproducible and collaborative data science in R' with Dr Tom Saunders and Dr Toby Johnson.
• A talk on 'Considerations for ethical and safe use of AI in health' with Associate Professor Rosie Dobson.
• A talk on 'Māori Algorithmic Sovereignty' with Dr Daniel Wilson.
• Case studies demonstrating innovative AI and data science techniques applied to research projects.
• A panel discussion on navigating the evolving skills landscape in AI and data science with Associate Professor Rosie Dobson, Associate Professor Jack Flanagan, Associate Professor Danping Wang, Associate Professor Anna Santure, and Mr Avinesh Pillai.

Friday 20 February

• A practical full-day introduction to using WEKA (Waikato Environment for Knowledge Analysis) and MOA (Massive Online Analysis), platforms that enable the application of machine learning methods to data within graphical user interfaces, led by Professor Albert Bifet.

Attendees will have opportunities to network with other participants and workshop leaders during meals and breaks.

Applications are open to all New Zealand:

• Doctoral candidates
• Early career researchers (less than eight years since highest qualification)
• Students intending to enrol in a doctoral programme in the next six months

Applicants will be expected to have some basic experience with Python, R, or a related programming language. Preference will be given to applicants who can clearly articulate how they will apply the skills they gain to their research, study, or job.

Places are limited and subject to a selection process. Applications closed on 1 December 2025, and applicants were notified of the outcome in December.

eResearch Engagement Specialist, Centre for eResearch
Email: Dr Tom Saunders

Research Data Support Services
Email: researchdata@auckland.ac.nz