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The University of Surrey is offering a fully funded PhD studentship on the topic of Audio/acoustics machine learning for intelligent sound reproduction, with industrial partner Bang & Olufsen
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transposable elements (TEs), major component of most plant genomes especially those large genomes. Deep-learning models (currently used for computer vision and natural language processing), which can encode high
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-machine manufacturing has experienced significant growth over the past five years, with projections indicating continued expansion. Improved efficiency can be achieved by design and materials optimization
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the effective and efficient design of safety-critical cyber-physical systems based on Machine Learning and Deep Learning, including deployment and applications of Large Language, Vision and Audio Models in
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. Knowledge or at least some interest in machine learning, preferably techniques for management/adaptation of systems. Programming experience in MATLAB/Python or C/C++, preferably in relation to radar signal
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of topics including, but not limited to, Machine Learning, Explainable AI, Network Visualization, Graph Drawing, and Dimensionality Reduction. Through our collaborative environment with experts in
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degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly between the labs of Prof
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Ledger Technology, Federated Learning, and AI. Affinity with programming, computer networks, and multi-actor systems. Interest or experience with research collaboration with other researchers and external
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the machine learning domain to improve data analysis You will be responsible for project meetings, reporting, scientific publications, and conference/seminar presentations You will supervise master/bachelor