162 cloud-computing-phd-student Postdoctoral research jobs at University of Oxford in Uk
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal
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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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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track
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will be required due to regulated activity involving children and ‘at risk’ adults. The successful candidate will hold, or have submitted a relevant PhD/DPhil (or equivalent) in a relevant discipline
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of Medical Sciences (AMS). Find out more about the Aye research and group here : About you Applicants must hold a PhD in Chemistry, Chemical Biology, or a related area (or be close to completion), prior
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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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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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will hold, or be close to the completion of, a relevant PhD/DPhil together with relevant experience. You will have experience in experimental high-pressure and/or high-temperature research, ideally with
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annum inclusive of Oxford University weighting Potential to under fill at grade 06RS: £34,982-£40,855 per annum inclusive of Oxford University weighting The Department of Computer Science seeks to employ
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at meetings/conferences. • You must hold a relevant PhD/DPhil in Pharmacology or neuroscience (or be close to completion) with experience in conducting in vivo mouse behavioural experiments