World’s Leading Machine Learning Course on Healthcare & Biomedical Sciences

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OxML Team

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Feb 26, 2025, 8:54:30 AMFeb 26
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Join the World’s Leading Course on Machine Learning in Healthcare & Biomedical Sciences

2–5 August 2025  | University of Oxford’s Mathematical Institute & Online

6th Oxford Machine Learning Summer School – OxML 2025

www.oxfordml.school


The MLx Health & Bio course covers the latest advancements in machine learning for health and biomedical applications. This module of OxML 2025 will feature some of the world’s top research studies in both ML theory and its applications in medicine and the life sciences.

Course Highlights

Participants will be introduced to cutting-edge biomedical foundation models (or several biomedical LxM) and attend lectures on the application of ML / representation learning and generative AI in following topics:

Application Topics:

  • Drug discovery

  • Genomics

  • Population health and epidemiology

  • Electronic health records (EHR)

  • Medical imaging

  • Wearable data for population health 

  • Biomedical text processing and NLP

  • AI models of the immune system

Theoretical Topics:

  • Statistical and probabilistic machine learning

  • Advanced representation learning (e.g., generative AI)

  • Geometric deep learning

  • Latest developments in computer vision

  • Advances in natural language processing (NLP) and large language models (LLMs)

  • Knowledge graphs, knowledge-aware ML, and neuro-symbolic AI

  • Real-world ML applications (e.g., alignment, interpretability, and ethics)

  • Survival and causal analysis in biomedical research 



Confirmed speakers:


  • Charlotte Deane (University of Oxford): Deep learning in proteomics and drug design

  • Michael Bronstein (University of Oxford): Geometric deep learning and ML for drug discovery and chemistry

  • Mirea Crispin (University of Cambridge): Multiomics

  • Arthur Gretton (UCL, DeepMind): Causal Machine Learning 

  • Aiden Doherty (University of Oxford): ML and large-scale wearable data to better understand the causes and consequences of disease

  • Jonathan Passerat-Palmbach (Imperial College London): ZKML, federated learning, and privacy-preserving ML

  • Hoifung Poon (Microsoft Health): Foundation models for medicine beyond NLP

  • Brian Hie (Stanford University): Biological Foundation models across all domains of life (Evo 2 and more)

  • Adam Lewandowski (UK Biobank): ML studies using multi-modal biobank data for population health

  • Rahul Krishnan (University of Toronto): Survival and time-to-event modelling

  • Vivek Natarajan (Google): Multimodal foundation models for biomedical applications and AI-driven scientific breakthroughs

  • Pierre Masselot (London School of Hygiene & Tropical Medicine): Machine learning in environmental epidemiology

  • More speakers will be announced soon.


Practical Workshop

Open-Source Tools for ML on Edge Devices and Robots led by:

• Vincent Moens (Meta)

• Remi Cadane (Hugging Face)

• Xuan-Son Nguyen (Hugging Face)


OxML is organised by AI for Global Goals in partnership with CIFAR and the University of Oxford’s Deep Medicine programme.

For more information, visit www.oxfordml.school or contact us at con...@oxfordml.school.



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