133 web-programmer-developer-"https:" "https:" "https:" "https:" "Newcastle University" Postdoctoral positions at University of Oxford
Sort by
Refine Your Search
-
challenges, from reducing our carbon emissions to developing vaccines during a pandemic. The Department of Experimental Psychology is a large, internationally recognised department with a high volume of
-
months. The project involves developing and applying a novel integrated platform to study the chemical molecular mechanisms and signalling consequences of reactive small-molecule metabolites within
-
samples and experimental models, with implications for autoimmune and metabolic disorders. As a Postdoctoral Researcher, you will primarily be responsible for the development, design, and execution
-
challenges, from reducing our carbon emissions to developing vaccines during a pandemic. The Department of Experimental Psychology is a large, internationally recognised department with a high volume of
-
as soon as possible but must be available to start by 1 April 2026 at the latest. This project aims to develop superconducting microwave interconnects and metasurfaces for distributed quantum networks
-
high-demand protective equipment application. You will be responsible for manufacturing and testing of materials, and development of a model to inform material design. You should possess a PhD in a
-
to their ongoing research programme, which aims to unravel the complex mechanisms underpinning 3-dimensional growth in plants. This is a fixed term position for one year. About you The successful applicant will hold
-
Victoria Nash and become a member of Nuffield Foundation Emerging Researchers Network. The Emerging Researchers Network supports early career researchers working on Nuffield-funded projects to develop
-
Postdoctoral Researcher. The group aims to identify, understand, and develop therapies for rare genetic disorders. The group is primarily computational but partners with multiple international labs (including
-
Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical