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mathematical models with state-of-the-art machine learning techniques to develop forecasting models that are more accurate, efficient, and capable of incorporating complex atmospheric phenomena. This is a fixed
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mathematical models with state-of-the-art machine learning techniques to develop forecasting models that are more accurate, efficient, and capable of incorporating complex atmospheric phenomena. This is a fixed
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The ProbAI Hub is a £8.5M research hub funded by EPSRC to develop better understanding of and new methods in AI. This will be achieved by research at the interface of AI and Mathematics
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PhD studentship in the Groups “Numerical Analysis and Scientific Computing” and “Mathematics Applied to Biology” at the University of Sussex (UK). PhD project Statistical inference has proved to be
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useful insights towards efficient numerical approximation of broader classes of differential equations. The successful candidate will be part of the Geometry and Mathematical Physics group at Loughborough
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addition to funding for tuition fees and research training. We are looking for applicants with a degree in Computer Science, Mathematics, Physics, or Electrical Engineering. Prior experience in tomographic imaging
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)) models are used at all stages of pre-clinical and clinical development, but they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a
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, Mathematics or Physical Sciences. Knowledge of numerical solutions of partial differential equations and/or fluid dynamics and good programming skills are essential. A Master degree in a relevant subject would
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Master’s degree (preferably with a merit or distinction) in a social, biological or mathematical subject, or computer science. UKRI Minimum Stipend Research Training & Support Grant Institutional & CDT
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they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a laborious task where highly qualified staff spend large amounts of time. Aims