134 computational-physics "https:" "https:" "https:" "https:" "University of Kent" Postdoctoral positions at University of Oxford
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verbal and written communication skills with all level of staff staff and an ability to operate effectively in a demanding research environment. Application Process You will be required to upload a CV and
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will contribute to an exciting, interdisciplinary programme developing next-generation human in vitro models of pain. The project aims to recreate the complex multicellular interactions that underlie
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, computer science, statistical or population genetics, or a related discipline), and a strong motivation to work on problems in genetics and you will also have relevant coding experience with producing high-quality
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We are seeking two full-time Postdoctoral Research Assistants in Machine Learning to join the Foerster Lab for AI Research group at the Department of Engineering Science (central Oxford). The post is funded by ERC (or UKRI) and is fixed term to 31 December 2028. We are seeking two candidates...
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the post and your skills and experience. You should possess (or be close to the completion of) a PhD in a relevant field (e.g. engineering, mathematics, physics or other relevant discipline). Previous
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available from as soon as possible. Application Process Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your application. In
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. Candidates will be interviewed for both posts through a single interview process. The successful candidates will have their own distinct projects but should also be prepared to work closely with each other and
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Process Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your application. In your supporting statement (****not more than 2
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, 12 Mansfield Road, Oxford, OX1 3TA and Rodney Porter Building, Sibthorp Road, off South Parks Road, Oxford, OX1 and is available from January 2026. Application Process Applications for this vacancy
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on combining theoretical and computational approaches (including data-driven mathematical models, tools for identifiability analysis and uncertainty quantification) to understand fundamental aspects