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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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people from non-technical backgrounds Experience with developing or deploying light weight models in environments with restricted resources (e.g. outside of HPC environments) Downloading a copy of our Job
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continuum modelling and finite-element simulations of multicomponent, multiphase electrochemical systems. • Ability to manage own academic research and associated activities • Previous experience
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modelling and finite-element simulations of multicomponent, multiphase electrochemical systems. Ability to manage own academic research and associated activities Previous experience of contributing
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System Models, or related simulation tools. Additional knowledge of statistical methods, Monte Carlo techniques, or ensemble approaches is highly valued. The post is advertised as full-time. We are open to
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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of the Solar Atmospheric Modelling Suite (SAMS) a next-generation, modular simulation framework for the solar atmosphere, tackling the chromosphere/corona problem. SAMS is being designed to incorporate world
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, advanced imaging techniques and numerical modelling. About the role A successful candidate will be working on the EPSRC funded project New perspectives in photocatalysis and near-surface chemistry: catalysis
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) Experience of working with multiple stakeholders in complex systems. Experience in large scale simulations Experience in Bayesian methods Experience using CRAFTY agent based model Full details of the role and
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/Simulink, or AIMMS 6. Experience conducting simulations, validation studies, or prototype development. 7. Ability to design, implement, and validate simulation models using appropriate tools and