Dates: July 6-14, 2024 (Oxford Mathematical Institute + Virtual)
Application deadline: 27 Feb 2024
Link to the application form: https://forms.gle/WjNykaMiaLXh2vWXA
For more info, please visit the school’s website: www.oxfordml.school
About OxML 2024- OxML is organised by AI for Global Goals, in partnership with CIFAR and The University of Oxford’s Deep Medicine Program.
- It will take place at the Mathematical Institute, University of Oxford, and online.
- OxML 2024 consists of three separate schools/modules:
- MLx Fundamentals (3-4 & 10-11 May, online): This module will provide all participants with the necessary background in fundamental theories and techniques behind modern ML.
- Representation Learning + Gen. AI (hybrid): This module will cover the advanced topics in deep learning (including, but not limited to generative AI) and its applications in language, vision, and more.
- Health+Bio (hybrid): In this, our speakers will cover the latest research and applications of ML in healthcare, biology, and more (e.g., ML in imaging, genomics, electronic health records (EHR), drug discovery, ... ).
We aim to host ~250 participants in person (plus ~250 virtually) in each module.
Note that, unlike the other two modules, the MLx Fundamentals module will not have a selection process; everyone can register on a first-come-first-served basis.
Speakers
The school’s world-renowned speakers are from top ML research groups. The first group of speakers’ bios and more details on their talks can be found on the school’s website; more speakers will be announced in the coming weeks.
You can follow the updates via our website, or Twitter and LinkedIn accounts.
Target audience
- Everyone is welcome to apply to OxML 2024 regardless of their origin, nationality, and country of residence.
- Our target audience is (1) Ph.D. students with a good technical background whose research topics are related to ML, plus (2) researchers and engineers in both academia and industry with similar/advanced levels of technical knowledge.
- All applicants are subject to a selection process; we aim to select strongly motivated participants, who are interested in broadening their knowledge of the advanced topics in the field of ML/DL and their applications.
Application
You can find the application for the school here.
Given the overwhelming number of applications we received in previous years, the application portal may close earlier than the deadline if the number of applications exceeds our capacity to review.
Best,
Reza Khorshidi, DPhil (Oxon)