128 phd-in-computational-mechanics-"Prof"-"Prof" Postdoctoral positions at University of Oxford
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the UKRI through the Frontier Guarantee Programme to Dr Jani R Bolla. The work is to be conducted in his lab in the Department Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB
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personal protection equipment (PPE). Your responsibilities will encompass developing new robotic benchmarking testing setup, hardware and controller of a robotic mechanical impactor, and data acquisition
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tomato and pepper as model systems. Work in Oxford will build on our extensive experience in studying bacterial virulence mechanisms and the role of the plant microenvironment in disease development
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Mobility Reading Group led by Nobuko Yoshida. The successful candidate will be located in the Department of Computer Science Reporting to Professor Nobuko Yoshida, the post holder will be responsible
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evaluations, attacks 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
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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We are looking to appoint a postdoctoral researcher, to work with a group of UK Higher Education Institutions to deliver a programme of mental health research. The work is funded by the Medical
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therapies. This role offers a unique opportunity to investigate the mechanisms of therapeutic resistance in glioblastoma and contribute to the development of more effective treatment strategies. Our research
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This is an exciting opportunity for an enthusiastic and self-motivated scientist to join the lab of Dr Katerina Toropova. The project aims to elucidate the molecular mechanisms of dynein-2 transport
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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