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year before the position expires, you will be offered an interview to clarify your future career. Description of the PhD position: The PhD research will focus on mathematical / computational modeling
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will lie on developing machine learning models for regression and reinforcement tasks to work with, enhance or replace established methods from computational engineering and computer simulation (such as
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model due to the mathematical challenge of solving the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and industrial partner
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AI models more interpretable and reliable by incorporating known constraints or physical properties. The successful applicants will be part of the Prob_AI hub and the School of Mathematics
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promise in understanding disease mechanisms and improving clinical decision-making. Recent studies suggest that generative models can uncover latent structures and improve classifier robustness across
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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Research theme: Applied Mathematics, Continuum Mechanics, Liquid Crystals Application deadline: All year round The successful candidate will join the PhD programme of the Department of Mathematics
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statistics/ mathematic background Strong programming skills in at least one major programming language Interest in applying relevant mathematical modeling techniques A collaborative team player with a desire
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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Application deadline: All year round Research theme: Control systems and theory, Applied Mathematics How to apply:uom.link/pgr-apply-2425 Number of positions: 1 Open to: UK This 3.5 year project is