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. Please note: while funding is available to cover this position, applicants are also welcome to apply for other scholarships during the application process. Eligibility We welcome applications from both UK
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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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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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context. The work will include, but is not limited to: investigating new mathematical formulations of the underlying physics; developing fast algorithms and numerical methods that leverage modern parallel
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a highly motivated candidate with: A first-class or upper second-class degree (or equivalent) in Materials Science, Chemistry, Physics, Chemical Engineering, or a related discipline. Experience in
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considered to be self-funded students for the purposes of admission. Applicants should have (or expect to obtain by the start date) at least a first class degree in an Physics, Mathematics, Electrical
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Arrangements: This is an in-person role based in Durham, requiring physical presence on campus and regular travel to partner schools in the region to support intervention delivery. The part-time hours (10 per
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modelling tools to understand and tailor the physical and chemical interactions at the interfaces within metascintillators. Cranfield University’s Centre for Materials is internationally recognised
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goals. Organise and facilitate interactive workshops and stakeholder meetings as part of the research process, generating qualitative and quantitative data to test and refine platform content and