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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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radiation of major groups and the impact that plants had on the Earth System. One approach to overcome the limitation of the fossil record is to use deep time ecological modelling to help simulate the early
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health. Specifically, our approach combines finite element modelling and medical image analysis. Our finite element brain models are based on tissue segmentation and our numerical simulations are validated
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Christopher Yau (http://cwcyau.github.io ) at the Big Data Institute, University of Oxford. This post will contribute to the development of a new simulation-based pre-training framework for building more robust
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production using historical and future climate simulations. The candidate will be expected to be responsible for conducting model simulations, interrogating results and integrating new processes and mechanisms
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Constrained experimental design Combining models and combining data / Realistic simulation of clinical trials Developing LLMs to utilise ODEs and ProbML as tools, Code synthesis for causality Generalisability
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We are seeking a talented and motivated Postdoctoral Research Associate (PDRA) to join the Energy and Power Research Group for a 12-month appointment to develop, implement and test a numerical model
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experimental design • Combining models and combining data / Realistic simulation of clinical trials • Developing LLMs to utilise ODEs and ProbML as tools, Code synthesis for causality
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partners, you’ll turn these insights into practical methods for smarter testing and control. You’ll need to have expertise in modelling and simulation of dynamic systems, strong programming skills, and the
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, and help integrate empirical data into system-level simulations. The project involves close collaboration with the University of Southampton on system modelling and NPL on advanced optical and thermal