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the UK Space Agency, European Space Agency (ESA), NASA and Teledyne e2v. A main focus for the CEI is the development and characterisation of detectors for space missions. One such mission is the Habitable
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computational scientists to develop advanced algorithms and models. Research and validate potential biomarkers associated with breast cancer progression, treatment response, or patient outcomes, using
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. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming, analysing and
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. Research Environment The project is in collaboration with two partners: (i) IDCOM at the University of Edinburgh, which develops theory, algorithms and hardware for the next generation of signal processing
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frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible. Multiobjective optimization algorithms will be employed to balance key performance indicators such as
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to undertake research in computational protein design. This will involve developing molecular simulation methods to optimise sequences for a variety of design tasks. Ensemble reweighting and alchemical
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development with Python Experience of machine learning with PyTorch Good knowledge of machine learning and computer vision algorithms Ability to work on own initiative and in a team Experience in collaborative
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group at King's College London led by Professor Bipin Rajendran. The group at King's is part of a consortium developing multiprocessor systems-on-chip with advanced nanoscale in-memory neural processing
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Intelligence for Humanity. Research – As a part of the Dyson School of Design Engineering, you will actively develop and lead your own research programme, in line with our research themes and vision. You will be
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Responsibilities Develop suitable algorithmic methods for live and real-time analysis of synchronous and asynchronous data. Write research reports and publications. Analyse and interpret the results of own research