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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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disease. Together with other members of the team, the post-holder will design parallel tasks for rodents and humans and apply comparable analytical approaches to data across species. Cell and circuit
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computer programs to design experimental paradigms, analyse data and conduct advanced statistical analysis. Prior experience in running neuromodulation studies including TMS and TUS is essential. You will be
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and Mind Building, South Parks Road, Oxford Applicants must hold a PhD in Microbiology and/or Molecular biology and will be responsible for providing microbiological data to facilitate the design of new
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and/or quantitative data, collaborate in the writing of research publications and represent the research group at external meetings/seminars/workshops and focus groups. The ideal candidate will hold a
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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take responsibility for the planning, execution and analysis of high-quality research, ensuring the validity and reliability of data at all times and will maintain ongoing scientific discussion with
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addressed to Prof. Ioannis Havoutis. For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ Only applications received before midnight on September 1st 2025 can be
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: paul.shearing@eng.ox.ac.uk For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ Only online applications received before midday on Tuesday 29 July 2025 can be considered
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a