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developed at Manchester to include heterogeneous magnetohydrodynamic phenomena (including current density localisation), solid-dynamics and fracture mechanics. The development of such a robust mathematical
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equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new optimization techniques, coding new algorithms, creating new mathematical
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complemented with mesoscale experiments involving connected patches of woodland communities to assess their reaction to change. Data from both experiments and the field will be used to inform computational
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with: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in
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-time Entry requirements The standard minimum entry requirement is 2:1 (Hons) in physics, chemistry, natural sciences, mathematics, computing, environmental sciences, or similar numerical subject. Start
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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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. We are looking for highly motivated candidates with a strong academic background in computer science, AI/ML, bioinformatics, or related fields such as mathematics and statistics. Informal enquiries
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(physics, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written). Knowledge in cryptography is desirable. Studentship and eligibility The studentship
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to how well they meet the following criteria: A first class or strong upper second-class undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after