176 parallel-and-distributed-computing-phd Postdoctoral positions at University of Oxford in Uk
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, including projects that could support future fellowship or independent position applications. Applicants should hold, or be close to completion of, a PhD/DPhil in biochemistry, molecular biology, structural
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shelves, the breakup of which can speed up flow of grounded ice and affect global sea level, and on the highly specialised Antarctic biodiversity. This ambitious programme brings together leading UK (BAS
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in top-tier scientific journals. It is essential that you hold a PhD/DPhil (or close to completion) in tumour immunology or a related life science field together with background in cancer research. You
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determined by the funding available. About you You should hold, or be near completion of, a PhD/DPhil in Molecular Microbiology, Biochemistry, Biophysics or related discipline. You must have substantive
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Programme Manager, using the contact details below. Only online applications received before 12.00 midday on 29th August will be considered. Interviews will be held as soon as possible thereafter
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hypotheses as appropriate, and contributing ideas for new research projects. It is essential that you hold a PhD/DPhil (or close to completion) in a relevant scientific discipline such as molecular biology
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development (ECD) and raise global visibility of climate impacts on ECD. The post holder will be a member of Climate Research Programme at ECI in SoGE, reporting to Dr Neven Fučkar, Senior Researcher, and there
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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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close to completion of a relevant PhD/DPhil, together with relevant experience; possess sufficient specialist knowledge in Socio-Legal Studies, Law of Evidence, Psychology or Psychiatry to carry out
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design