54 scientific-computing Postdoctoral research jobs at University of Oxford in United Kingdom
Sort by
Refine Your Search
-
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
-
Wellcome Trust and by project-specific funding from the EU Horizon programme. As part of a multi-disciplinary research team, you will contribute to analyses of the global food system. Some of the interests
-
Institute for Molecular and Computational Medicine (IMCM). You will test GSK assets and targets in established models of podocyte and mesangial cell pathology relevant to glomerular diseases. You will
-
to the selection criteria. The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
-
. Concurrently, you will develop lower order analytical models and perform high fidelity computational simulations to corroborate experimental findings and propose other configurations to be subsequently
-
supervision, are self-motivated and have strong computational and scientific writing skills. We provide a nurturing environment and access to high-dimensional pathogen genome, human mobility, epidemiological
-
the advertised position), CV and the details of two referees as part of your online application. The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science
-
and Prof Paul Shearing. The post is funded through a strategic research partnership and is fixed term for up to 2 years. To support the programme, the post holder will be required to carry out research
-
records of experimental work and findings. You will take initiatives in the planning of research; conduct and plan own scientific work with appropriate supervision and present findings to colleagues within
-
and science exploitation of the MIGHTEE survey data. The postholder would have the opportunity to identify new discoveries in the data and would be ideally placed to lead the science based on the data