15 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at University of Leeds
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This role will be based on the university campus, with scope for it to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements. Are you a Computer Scientist
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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scientist looking to apply your expertise to real-world forecasting challenges in Africa? Machine-learning has the potential to revolutionise weather prediction in Africa, and we are seeking a scientist who
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Universities? You will join a collaborative programme with Merck Electronics KGa, a world-leading company working in liquid crystals. You will work with a team of scientists from the company along with Dr
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The 6G National Research Programme is at the forefront of pioneering research and development in the field of 6G technologies. As part of the Communications Hub for Empowering Distributed Cloud
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University to focus on data collection in the North East. The two research fellows will work closely together. You will have a PhD (or near to competion) in Nutritional Epidemiology or a closely allied
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large team with colleagues in Leeds studying other aspects of blood clot structure and function and their influence on thrombosis. You will have a PhD in molecular biology, cell biology, biomedical
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have a first degree in one of the following subjects; biological sciences, environmental science, ecology, geography, soil science or agriculture, and a PhD in soil science, sustainable agriculture, agri
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their privacy. The villa was a remarkable example of their collective vision, where every room was meticulously curated to reflect their tastes and passion for art and objects. - each room was densely filled with
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can support both health and mobility outcomes. The successful candidate would be responsible for the more technical parts of this project, leading the computational modelling of charging infrastructure