192 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United Kingdom
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward
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generative Large Language Models (LLMs), as well as Machine Learning (ML) tools — to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS hospitals
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design and implementation of visual cues detection on video datasets (face and gesture), context-aware multimodal analysis, machine learning/self-supervised learning for automatically detecting subtle
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Overview of the Role Are you experienced in machine learning and looking to apply your skills to solve new challenges and reduce disaster risk? Do you want to further your career in one of the UKs
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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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About the Role A fantastic opportunity has arisen for a Senior Research Fellow to join the Power Electronics, Machines and Drives Research Institute (PEMC) at the University of Nottingham and become
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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unit and individual and collaborative research in the area of Power Electronic, Machine and Control. The role holder will be expected to conduct and lead high-caliber, impactful research at the forefront
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research. About the role: We are seeking a data scientist with extensive expertise in statistics, machine learning and AI, and with experience in mental health research and the analysis of electronic health