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world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description: Responsive 3D
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motivated applicant to undertake an original and applied programme of research linked to ongoing work led nationally by the Chartered Institute for the Management of Sport and Physical Activity (CIMSPA
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DEPARTMENT OF HEALTH TECHNOLOGY AND INFORMATICS Research Assistant Professor in Medical Laboratory Science / Biomedical Science / Medical Imaging and Radiation Science / Medical Physics / Medical
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complex input. For instance, in physics-informed ML, in addition to data examples used by a standard ML setup, domain knowledge serves as an additional input. It can be in an explicit form of rigorous
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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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subject relevant to the proposed PhD project (inc. Mechanical Engineering, Aerospace Engineering, Chemical Engineering, Applied Mathematics and Physics). Ability to undertake scientific programming (e.g. in
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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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a collaborative studentship between the University of Edinburgh and the National Physics Laboratory (https://www.npl.co.uk/ ). The position will be registered and hosted at the University of Edinburgh
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information about the application process and any adjustments you may require; recruit@mrc-lmb.cam.ac.uk.