29 processor-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions in United Kingdom
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We are seeking an ambitious and highly motivated Research Fellow in Computer Vision to contribute to an EPSRC-funded project, LungSight, focused on visual and acoustic screening for early detection
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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Principal Investigator (PI) to ensure all project deliverables are met. Job Requirements A Ph.D./Master’s degree in Computer Engineering, Communications Engineering, Computer Science, or a highly related
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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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the group can test and validate models of sodium-ion battery behaviour. As such, proficiency in computer programming (particularly python) is required as well as knowledge of numerical methods
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laboratories, dedicated PGR facilities along with study and breakout areas. With a strong emphasis on employability, the business and law programmes offer students an opportunity to undertake a placement
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trading floor, mock and real courtrooms, computer laboratories, dedicated PGR facilities along with study and breakout areas. With a strong emphasis on employability, the business and law programmes offer
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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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, computer vision, and predictive modelling, alongside excellent IT, analytical, interpersonal and communication skills in spoken and written English. You must be able to collect, process and present data with
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Interaction (HCI) and social science methodologies to lead the user research and policy development, as part of an interdisciplinary team investigating harmful user-generated content in virtual worlds as part