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This project provides an excellent opportunity to develop state-of-the-art mathematical models and computational tools of emerging respiratory pathogens, within a world-renowned research group
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About the Project Applications are invited for a PhD position in “Probabilistic Artificial Intelligence” at the School of Mathematics, University of Bristol. Please visit the page below to see
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Applications are invited for a fully-funded 42-month PhD studentship with Dr Rachel Nicks and Prof Stephen Coombes on the Leverhulme Trust-funded project White Matter Computation: Utilising Axonal
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background in Computer Science, Mathematics. Students with interests in machine learning, deep learning, AI, uncertainty quantification, probabilistic methods are encouraged to apply. For eligible students
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degree or a master’s (or international equivalent) in a relevant science, mathematics or engineering related discipline. Excellence in computational science and mathematics Programming skills in any
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PhD Studentship in Analysis of PDE Supervisors: Sugata Mondal Second advisor: Michael Levitin Project Overview: Spectral geometryis the area of mathematics where one studies inter-relations between
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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience
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, including engineering, mathematics and the physical sciences. Students should be able to demonstrate aptitude for computer modelling and enthusiasm to address real-world problems of great policy significance
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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to exploit approximate or computational solutions; however, this can be unsatisfactory in that it lacks in valuable physical insight. This insight is often crucial in changing partial mathematical solutions