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Honours degree (or equivalent) in an appropriate discipline such as Computer Science or Mathematics. Applicants are expected to have excellent mathematical skills as well as an interest in discrete
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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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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence will inform future race strategy and live race tactics. Multiple factors influence the strategy...
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Communications Dr Jessica Jay, School of Mathematical Sciences Dr Dan Fretwell, School of Mathematical Sciences Qualifications and Experience We are looking for motivated individuals who are eager to tackle real
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should have or expect to achieve, at least a 2:1 (or equivalent) in any engineering degree programme, physics or mathematics. English language requirements: Applicants must meet the minimum
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boundaries. This fully funded PhD scholarship is suitable for students with a background in Engineering Design, Smart Manufacturing, Aerospace Engineering, Mechanics, Computer Science, Mathematics, Life Cycle
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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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to focus on the relationship between geometry and quantum theory. A key objective will be the conceptual and mathematical understanding of the original Penrose spin network, with a view toward foundational
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motivated candidate with a strong mathematical background, particularly in one or several of the following areas: multivariable control, nonlinear control, robust control, matrix analysis, and convex