164 postdoc-parallel-computing research jobs at University of Oxford in United Kingdom
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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
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Family leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of social and sports clubs Discounted bus travel and Season Ticket travel loans How to apply
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FOR INTERNAL APPLICANTS ONLY About the role The Department of Social Policy and Intervention is seeking a Research Assistant to join an the OUR SPACE research team, led by PI Bridget Steele. The Research Assistant will be responsible for leading an evaluation of programming to reduce sexual...
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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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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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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
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with expertise in obstetrics/obstetric medicine to play a senior role in delivering this highly clinically important research programme. The role will give you wide exposure to different research
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multidisciplinary programme of work examining each level of the sensory chain, including detection, signal transduction and amplification, cellular and behavioural responses. Our combined expertise includes quantum
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computational social choice, and aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will
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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