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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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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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, 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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and advanced material design and fabrication. Through this multidisciplinary project, the student will develop expertise in: Hands-on experience with advanced computational physics and materials
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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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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(e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) Willingness to adapt and work across different disciplines Ability to work independently and cooperatively Commitment
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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
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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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the current thermo-mechanical process use to strengthen the current generation of crush alloys. Programme will use different thermomechanical processing paths including heat treatment and more complex paths