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are welcome to apply but will be required to cover the difference between Home and International fees. International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate
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, Physical Sciences, Chemistry, Natural Science, Mathematics. Mode of study Full-time Start date 1 October 2026 Funding This PhD project is in a competition for a Faculty of Science funded studentship. Funding
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wellbeing and enabling inclusive decision-making for a greener, fairer and healthier future. The PhD will be based in the Environmental Mathematics group within the Department of Earth and Environmental
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, engineering, mathematics, or related subject) Proficiency in English (both oral and written) Essential to have strong foundations in computer systems through degree courses or equivalent work experience
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is critical for a wide variety of engineering and environmental applications, remains unexplored. You will join a team of researchers that experimentally quantify the flow-physics of fundamental
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necessary. Applicants will have a BSc degree/MSc in Computer Science, Mathematics, or a similar computational field. Funding This four-year studentship is funded by Cancer Research UK Cambridge Institute and
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undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and spoken communication skills The following skills are desirable but not essential: Background in
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profile We welcome applicants with backgrounds in computer science, applied mathematics, or engineering. Essential: strong Python, deep learning experience (PyTorch), and foundations in calculus/linear
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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
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ODEs with convergence guarantee and uncertainty quantification,” Mathematics of Computation, Jun. 2025, doi: 10.1090/mcom/4120, https://arxiv.org/abs/2404.19626 C. Offen, S. Ober-Blöbaum, “Learning