199 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at University of Nottingham
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well as extensive experience in data analytics/advanced statistics/machine learning is desirable. Research experience in flavour science and/or food chemistry is advantageous. As a people-orientated individual, you
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understanding and process optimisation. The work will primarily feature the integration of high data-density reaction techniques, laboratory automation & robotics and kinetic/machine learning modelling
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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this information-gathering process. The successful applicant will have strong expertise in programming, and in particular developing AI-based computer vision methods. Ideally, they will have experience
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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and testing a prototype tool with young people, practitioners and computer scientists to support improved identification, understanding and support for self-harm in young people. You will support the
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. Previous experience working with computer-booking systems would be desirable. The role is key to ensuring a first class and seamless experience for our student, staff, alumni and public members. Excellent
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Testing Technical Apprenticeship to learn the skills needed to support the operational, research and teaching requirements of the materials laboratories across the Mechanical, Materials, and Manufacturing