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slow sand filters. This project suits graduates seeking careers in drinking water technology, sustainable infrastructure, and low carbon process design. Drinking water production is under mounting
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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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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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in Physics, Maths, Engineering, or a related discipline. Be familiar with differential equations and have some
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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should be made online via the above ‘Apply’ button. Under programme name, select School of Sport Exercise and Health Sciences. Please quote the advertised reference number: SSEHS/SRLJ25 in your application
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the Department of Physics and Astronomy at the Streatham campus in Exeter. The UK Government has undertaken a assessment of the potential of metamaterials science and technology, which is available here . Due
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). The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description