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of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject (physics
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defined by Swansea University) in Engineering, physical sciences or similar relevant science discipline. We also welcome applications from graduates in computational science or mathematics. Note for
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling to pioneer innovative sealing solutions. What We Offer Full 4-year Funding for UK applicants
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51 Faculty of Physics Startdate: 01.09.2025 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.08.2029 Reference Reference no.: 4391 We are a
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-state physics, fluid dynamics, solid-dynamics, and fracture/degradation; all in a highly transient and non-linear system. In this project we will extend multi-component, multi-phase field frameworks
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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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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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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