202 application-programming-android Postdoctoral positions at University of Oxford in Uk
-
application of conditional diffusion models, flow matching techniques, or related generative approaches, as well as experience working with probabilistic (Bayesian) methods and statistical modelling. Strong
-
flexible working can be considered. Diversity Committed to equality and valuing diversity. Application Process You will be required to upload a supporting statement and an up-to-date CV as part of your
-
mathematical skills, a strong understanding of mechanics and an ability to undertake scientific programming. You will have excellent written and oral communication skills, and an ability to work both
-
to a large-scale, interdisciplinary research programme. We are looking for someone with proven expertise in a fast-paced environment, who is committed to delivering high-quality research support and
-
, particularly in live bacteria or at the single molecule level; programming commensurate with quantitative fluorescence microscopy analysis and single molecule tracking; molecular bacteriology; recombinant DNA
-
considered for less experienced but highly motivated applicants who demonstrate exceptional potential. Candidates who do not fully meet the requirements for a Grade 8 post may be appointed at Grade 7: £39,424
-
research programme on “Enabling consumers to make healthy financial choices”, focusing on how technological and organisational solutions can improve financial literacy and decision-making. This post, under
-
strategic programme. Through multiomic and spatial biology exploration of temporally distinct samples from clinical trials and advanced biological models, an international consortium of leading colorectal
-
Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to
-
Raman’s cardiovascular research team. This role is embedded within a cutting-edge programme focused on integrating high-dimensional datasets, including advanced cardiac MRI (oxygen-sensitive, metabolic, and