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of statistical algorithms. Duties include undertaking your own programme of research and assisting with ongoing research programmes, using databases, modelling, and computation as appropriate; writing up results
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principles from natural evolution, such as modularity, gene amplification, or cooperation, to help engineered organisms explore richer evolutionary pathways Martin Spinck – The Spinck group explores biological
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solvers • Implementing and analysing online optimisation algorithms for real-time grid balancing • Liaising with project partners (NESO and University of Strathclyde) Essential selection
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to trace how welfare algorithms operate in practice. They will also contribute to comparative analysis across case study countries, support interdisciplinary collaboration, engage with external stakeholders
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learning models to accelerate mixed-integer solvers Implementing and analysing online optimisation algorithms for real-time grid balancing Liaising with project partners (NESO and University of Strathclyde
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modern genetic datasets and functional genetics now available to trace the evolutionary history of production and sustainability traits over 10,000 years. Using selection analyses, the research will
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, with nearly 40 permanent academic staff working within and across social, evolutionary and health anthropology. Each year, we welcome over 130 undergraduate students and around 70 postgraduate students
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials
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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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under the supervision of Professor Rachel Humphris. They will lead in-depth ethnographic fieldwork in the Netherlands, undertaking interviews and participant observation to trace how welfare algorithms