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the scope of the provisions of the collective bargaining agreement. Your qualifications Must-haves A Master’s degree (completed or near completion) in Computer Science, Machine Learning, Mathematics, Physics
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completeness. In other instances, where sufficient data do exist, the models used in attempts to glean performance insight may be overly simple and violate mathematical or statistical assumptions or be overly
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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of neuroscience and new computational methods, combining mathematical and biophysical models with state-of-the-art diffusion and functional MRI data, in typically and atypically developing populations through
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Application deadline: All year round Research theme: Computational Mechanics/Applied Mathematics How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded and home students
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operation. This is an exciting PhD project with industrial collaborators at the intersection of power systems, artificial intelligence, and mathematical modelling. The project is well-suited to students with
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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/Associate, who will work with Professor Paul Bushby and Professor Tamara Rogers on the STFC-funded project “Magnetism in Hot Jupiters”. The successful candidate, who will be based in the School of Mathematics
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publication record. Excellent mathematical and programming skills are essential, with experience in two or more of deep learning, deep generative models, chemistry, biology. Interviews are expected to happen in
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to genuinely group-level interactions — in human populations, in multi-agent AI systems, and in animal societies? Can the same mathematical framework describe convention formation in online human groups