ELLIS Summer School at Unit Manchester
The Summer School aims to provide introductions to Probabilistic ML and Causal ML during the first day, and then two days focused on specific healthcare and biology technologies.
Day 1: Probabilistic ML and Causal ML (e.g., Gaussian processes, probabilistic deep learning including VAEs, causal graphical models, potential outcomes framework, etc)
Day 2: Omics Data Analysis (e.g., single-cell, genomics, methylation, proteomics, etc)
Day 3: Longitudinal data and Electronic Health Records
Lectures in the morning, lab session in the afternoon, research-oriented talk to finish the day. We will aim to include industry talks from researchers at DeepMind and AstraZeneca.
Contact: Mauricio A Álvarez
This is part of the 2026 ELLIS Winter & Summer School Program