Sort by
Refine Your Search
-
upskill on algorithmic information theory, AIXI, Bayesian statistics, and reinforcement learning theory (existing expertise on these topics not required). Proven ability to independently design, build, and
-
at an international level? Can you contribute to innovative research‑led teaching and support an excellent student experience across undergraduate and postgraduate programmes? Are you committed to working
-
impact and excellence, and serving as a hub for many funded networks. As a research-led department, our high-calibre staff produce innovative and technically demanding research on a world stage spanning
-
, you will: - Conduct and publish innovative, internationally leading research within your field. - Contribute to teaching and curriculum development at undergraduate and postgraduate levels. - Supervise
-
Moss to: Develop machine learning emulators for the WAVI ice-sheet model to serve as efficient surrogates for large-scale Bayesian inference. Develop utility-function-based experimental design methods
-
development facility in the Oxford Science Park, including GBI. EIT is committed to cultivating a community where excellence is achieved through collaboration, trust, innovation and tenacity. We foster
-
career, collaborate across disciplines, and inspire the next generation of mathematical scientists. What you would be doing: As a member of our academic faculty, you will: - Conduct and publish innovative
-
, distributed training, cloud compute, or cluster environments; have experience with large language models, either through training, fine-tuning, evaluation, inference, tooling, or deployment; are able to design