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transport and recombination, and help integrate empirical data into system-level simulations. The project involves close collaboration with the University of Southampton on system modelling and NPL
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proteins — offering unprecedented insight into disease mechanisms, therapeutic response, and patient stratification. As clinical diagnostics move toward more personalised and preventative models, it is
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innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery
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of education programmes. About the role Applications are invited for a postdoctoral position in the group of Dr. Chiara Gattinoni — within the Theory and Simulation of Condensed Matter research group
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. Track record of international collaborations. 5. Research experience with modelling organic molecules or polymers. Downloading a copy of our Job Description Full details of the role and the skills
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub
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of semiconductor devices in a clean room using advanced fabrication techniques and developing device simulation TCAD models to complement experiments and to support device design and to analyse device failure
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Responsibilities To undertake training to run CONDOR simulations and in biophysics as required. To run and analyse CONDOR simulations on our high-performance computing cluster. To develop a deep-learning model for
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techniques and numerical modelling. About the role A successful candidate will join the EPSRC-funded Programme Grant Next Generation Metamaterials: Exploiting Four Dimensions (META4D: www.meta4d.co.uk