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individually, make a real difference. The role An exciting opportunity for a postdoctoral Research Fellow with a background in mathematical modelling / epidemiology has become available in the Faculty of Health
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or equivalent experience in an appropriate discipline A background in numerical ice-sheet, glacier or fracture modelling, or equivalent experience Robust experience with computer coding (e.g., Python, C++) Track
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around us. The Role As a Research Fellow, you will collaborate with leading experts across three international labs—spanning Coventry University’s Centres for E-Mobility and Clean Growth and Computational
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this aim and to collectively, and individually, make a real difference. The role An exciting opportunity for a postdoctoral Research Fellow with a background in mathematical modelling / epidemiology has
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students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration
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interdisciplinary team on developing high performance urban farming module via computational and empirical analysis Support in the design and maintenance of the vertical farm to be setup in SIT@Dover and willing
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toxicological cross-species metabolomics resources. Drive the in-depth computational characterisation and annotation of metabolomes across diverse model organisms and human cell lines, using multistage
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. You will also be responsible for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. You will also be
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reinforcement learning, computational rationality and user modelling, and simulator-based inference. The post-holder will work on a project from Professor Kaski’s UKRI Turing AI World-Leading Fellowship. Research
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modellers using advanced simulations to interpret and validate observations via data assimilation. There will be opportunities to spend time with project partners at UCLA (Prof. James McWilliams) and attend