214 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at University of Nottingham in United Kingdom
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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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(CHF), tailored to complex geometries typical of fusion reactor cooling systems. Compile a comprehensive dataset of boiling parameters to support machine learning-based analysis of two-phase flow
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, together with evidence of managing cash-handling/reconciliation processes. Previous experience working with computer-booking systems would be desirable. The role is key to ensuring a first class and seamless
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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
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to cover living costs; Join a multidisciplinary cohort to benefit from peer-to-peer learning and transferable skills development. Learn more about the programme, available projects, and the application