14 - 18 September 2026
White City Campus, 51³Ô¹ÏÍø
Exposome Analytics will be held at the School of Public Health, 51³Ô¹ÏÍø from the 14 to 18 September 2026. Each day begins with lectures introducing theoretical concepts, followed by a seminar and a practical session to illustrate these concepts: Computational Epidemiology, Causal Thinking, Machine Learning, Artificial Intelligence, and Deep Learning.
Learning outcomes
After Exposome Analytics, students will be:
- familiar with most OMICs profiling approaches and their extensions
- able to implement these approaches to analyse real data, including in case of complex study designs
- able to integrate different OMICs data in relation to an outcome of interest using regression and correlation approaches
- able to infer network topologies for results interpretation and feature selection
- able to perform validation, sensitivity and stability analyses using resampling techniques
Who would benefit
Exposome Analytics is designed for academics (students and researchers) and industry scientists (pharmaceuticals, insurance, food industries) with experience in high-throughput data analysis. Ideal candidates include former MEC or STAT-XP students seeking to deepen their knowledge in data interpretability and integration. Proficiency in basic statistics, OMICs data, and R statistical software is desirable.
Participants should bring their own laptops.
There is space for 40 participants.
Keynote speakers
Professor Marc Chadeau-Hyam
Professor of Computational Epidemiology and Biostatistics, School of Public Health, 51³Ô¹ÏÍø
Professor Roel Vermeulen
Professor, Veterinary Medicine, Department Population Health Sciences, Utrecht University
Professor Benoit Liquet
Professor, School of Mathematical and Physical Sciences, Macquarie University
Course fees
£1300 for IHEN members and Exposome projects
£1500 academics
£2000 Private