601 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "Computer Vision Center" Fellowship positions in United Kingdom
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they may need to further develop (and for which we will provide support). The applicant will also be expected to work side-by-side with staff recruited in computer science and the wider academic team
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conferences in areas of machine learning, computer vision, and Large Language Models and high-impact specialist peer reviewed academic journals. • Ability to conduct interdisciplinary research activities
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-intensive Universities? As a Research Fellow in Computational Climate Politics you will work on the UKRI FLF project “Understanding normative change to address the climate emergency ”. This is a 4+3 grant
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on delivering high-quality teaching and diverse, real-world research. We specialise in biosciences, chemistry, computing and technology, as well as engineering, forensic science, mathematics, physics
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the Project PI. ii. Meeting the deliverables by carrying out the computational simulations and experimental studies planned for under the scope of work of the projects within the timeframe to meet the
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, together with relevant experience • Possess sufficient specialist knowledge in the marketing discipline to work within established research programmes • Ability to manage own academic
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to the planning and organising of the research programme and/or specific research project Co-ordinate own work with others to avoid conflict or duplication of effort Knowledge of the protected characteristics
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to develop research programmes and methodologies. The successful applicant will also be able to work collaboratively, supervise the work of others and act as team leader as required. Applicants will be
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, Applied Mathematics, Physics, Acoustics, Computational Science or a closely related discipline. Strong experience in numerical/computational modelling (e.g., FEM/multiphysics, wave propagation
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experience in Mechanical Engineering, Applied Mathematics, Physics, Acoustics, Computational Science or a closely related discipline. Strong experience in numerical/computational modelling (e.g., FEM