We have room for 1 or 2 outstanding machine learning Ph.D. students to join our elite group at the University of Cambridge in 2020.
We are looking for:
leaders who want to realize their full potential and shape the future of machine learning
explorers who think boldly and prefer pushing boundaries to sitting still
builders who see projects through to completion and want to make a real-world impact
5 ways we can empower you
1. Fully funded
All positions are fully funded for 4 years, thanks to the generous support of our partners, including GlaxoSmithKline, AstraZeneca, the Office of Naval Research, and the Cystic Fibrosis Trust (more here). Funding covers both home and international fees in addition to living costs/stipend.
2. World-leading research and tuition
Mihaela van der Schaar is one of the foremost names in machine learning, and the University of Cambridge is the absolute pinnacle of academia.
We’re a small group, but we punch well above our weight. Our 2 postdocs and 10 Ph.D. students have 18 papers accepted at the four largest AI and machine learning conferences (AISTATS, ICLR, ICML and NeurIPS) in the last year alone.
3. Freedom to think big and explore
We are creating new frontiers in machine learning. Despite our primary focus on medicine, we produce ground-breaking work across an enormous range of machine learning sub-fields – from new deep learning theory and algorithms to methods for causal inference, graphical models, statistical machine learning, time series data, interpretable machine learning and reinforcement learning.
4. Projects with a purpose; work that can change the world
Our research projects are targeted and practical. Our mission is to apply machine learning to real-world problems in healthcare, and our goal is nothing short of a revolution in medicine.
5. Unmatched prospects
Employers know that our lab only takes the best and brightest. When you graduate, you won’t need to settle: our alumni around the world have become leaders in their fields, with some continuing to full professorships and others joining top private-sector teams including Google, Intel, Qualcomm and Apple.
Eligibility and application process
Positions will be within the University of Cambridge’s Department for Applied Mathematics and Theoretical Physics, and will start (remotely) from autumn 2020.
Admission is competitive, and successful candidates will need to have top grades from world-leading academic institutions, with excellent mathematical backgrounds and preferably experience in machine learning. No knowledge of medicine or biology is required.
Applicants should hold (or be predicted to achieve) the equivalent of a first-class undergraduate degree with honours in a course with a strong quantitative component (e.g. engineering, comp sci, mathematics, economics, etc.).
Please contact us using the form below, providing links to your resume and any relevant publications, reports or code if these are available.