191 maynooth-university-programmable-city-project Postdoctoral positions at University of Oxford in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Field
-
We are excited to offer this Postdoctoral Research Associate position at the University of Oxford, under the supervision of Professor Paul Goldberg and Dr Markus Brill from January 2026. This is a
-
of Chemistry, University of Oxford, for a period of up to 2 years. The project involves the synthesis of synthetic supramolecular transport systems for ions and other polar molecules, that are based on stimuli
-
The University of Oxford is seeking a Postdoctoral Researcher to join our laboratory team in the Radcliffe Department of Medicine (RDM) Division of Cardiovascular Medicine. RDM-Cardiovascular
-
to the supervision of graduate students working on the project - Contribute to the preparation of academic publications. - Contribute to code development efforts in the group at large About you The
-
. This project explores the emerging risk landscape posed by the deployment of autonomous LLMs that can execute tasks, manipulate system settings, and interface with web services—moving beyond mere text generation
-
research team investigates molecular mechanisms underlying viral evolution and host changes. You will be working on a project that will focus on understanding how some viruses can change their receptor
-
This is an exciting opportunity for a post-doctoral researcher to join a research project based in the Department of Education, University of Oxford. The project aims to explore whether higher
-
generate key structural and biophysical data to support the design of small molecule inhibitors with particular focus on protein production and crystallisation, solving protein-ligand structures, fragment
-
funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
-
with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly