175 phd-computer-artificial-machine-human Postdoctoral positions at University of Oxford
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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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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scientific discipline—particularly in healthcare data science, medical informatics, or clinical machine learning—as well as demonstrated expertise in healthcare data analysis, machine and deep learning, and
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Computational Neuroscience and related fields as part of the Medical Research Council, UKRI grant “Algebraic topology bridging the gap between single neurons and networks”. They will be expected to conduct
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machine learning. This particular thematic area will be supervised by Associate Professor Agni Orfanoudaki. You will be responsible for planning and managing your own research programme within
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About the Role We are seeking an experienced and highly motivated senior postdoctoral researcher in computational biology. The successful candidate will join a multi-disciplinary team working in
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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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We are seeking a highly talented and experienced Postdoctoral Researcher to join a research team led by Prof Chris Summerfield focussed on studying learning and decision-making in humans and machine
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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity