408 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" research jobs in United Kingdom
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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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a possible extension for one more year. The starting date is November or December 2025. This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological
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machine learning model to rule out heart attacks in the emergency room, which has the potential to translate to large savings for healthcare systems in the world, (2) a computational modelling to assist in
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background knowledge in statistical genetics, machine learning, omics data analysis, and computational biology. Additional knowledge in transcriptomics, statistics, and foundation models is also desired. Fixed
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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
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machine learning model to rule out heart attacks in the emergency room, which has the potential to translate to large savings for healthcare systems in the world, (2) a computational modelling to assist in
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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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. The Department of Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Surface Structures The Data-driven Atomistic Simulation (DAS) group, led by