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Learning algorithms (clustering algorithms (K-means), genetic algorithms, and reinforcement learning) and end-user piloting of software systems – including technical attributes and legal/commercial
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-aware AI, HR analytics and logistics, optimisation techniques for labour and warehouse management. Experience of applying Machine Learning algorithms (clustering algorithms (K-means), genetic algorithms
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statistics, AI, and computation to generate biological and medical insight. The group focuses on the development of novel algorithms, tools, and databases that are open source and freely available to all users
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Evolutionary algorithms or genetic programming Financial compliance, regulatory technology, or financial crime prevention domain knowledge Adversarial machine learning or AI security Personal attributes: Strong
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optimisation algorithms for quantum routing using genetic algorithms (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO), optimising cost functions subject to entanglement fidelity
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on high-fidelity modelling and test data for both metals and thermo-set composite materials. To achieve this we will explore the use of advanced genetic algorithms and/or Artificial Intelligence (AI
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the neural mechanisms underlying goal switching and behavioural strategy selection, linking algorithmic theories of behaviour to defined microcircuits and pathways. The position will employ a multidisciplinary
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. Experience of optimising training/inference of deep learning models. Experience with databases e.g. PostgreSQL, data visualisation and image alignment algorithms. Familiarity with the use of containers e.g
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Analysis Machine Learning Genetics Molecular Biology References: Developmental mitochondrial complex I activity determines lifespan. Stefanatos R, Robertson F, Castejon-Vega B, Yu Y, Uribe AH, Myers K