Sort by
Refine Your Search
-
properties of Li-rich three-dimensional materials for lithium battery cathodes using density functional theory (DFT), molecular dynamics, cluster expansion, machine learning computational techniques. This work
-
The Oxford Applied and Theoretical Machine Learning group at the Department of Computer Science has a new opening for a Project Support Officer, working together with Professor Yarin Gal. In
-
A postdoctoral research associate position is available for a technically strong researcher to join the Oxford Machine Learning in NeuroImaging (OMNI) lab at Oxford’s Department of Computer Science
-
Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
-
to scientific questions and must be able to rapidly acquire skills in new programming languages, libraries and technologies. Any prior experience working with frontend/backend web development, machine learning
-
applications. Applications are sought from across a diverse set of disciplines under the Information Engineering umbrella, including, for example, physics-informed machine learning and AI, computer vision
-
and its end-users. You will remain abreast of new developments in data science and data visualisation, in particular the use of machine learning and AI tools, and their application to IDDO’s model. You
-
, ELISPOT, flow cytometry, B and T cell receptor sequencing, and transcriptomics. You will develop a reproducible informatics and machine learning pipeline to process large volumes of sensitive trial data in
-
-contact manipulation/locomotion, machine learning and optimisation, avatar animation or related areas. You have experience working on real robots and great team working skills. Informal enquiries may be
-
We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris