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infectious disease epidemiology and mathematical modelling in Biology and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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Almost all radar systems currently transmit from the same location. This kind of radar modality has been optimised for decades, however the challenge to detect very small and very fast objects
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
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indicators beyond current proxies. High-Speed Rail (HSR) and National Spatial Optimisation Examine how HSR infrastructure reshapes urban and regional population distribution, and develop a multi-objective
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When robots move, human interaction partners and observers ascribe an intention to the robot. For example, in a simple pick-and-place scenario where a robot is facing two different objects, as its
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providing a basis for decision support and lifetime extension. This may be obtained by comparing existing design practice with results based on application of Bayesian updating to account for uncertainties in
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expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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the integration of research findings into the broader Sliding Lands project. Key research objectives include: Building a time-series data cube of landsliding across New Zealand using satellite imagery archives