44 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" Fellowship positions in United Kingdom
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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, funded by a Leverhulme Trust Research Leadership Award held by Dr Alessio Spurio Mancini. ECLIPSE's goal is to develop next-generation inference frameworks that combine machine learning with rigorous
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statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; b) work on sleep datasets exploring
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collocates Hawkes (formerly CMIC), UCL’s AI Centre (AIC), and UCL’s Advanced Research Computing Centre (ARC) creating a vibrant hub of data-science researchers with interests from basic machine learning and AI
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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R
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development of Northern Ireland. Our core business activities are teaching and learning, widening access to education, research and innovation, and technology and knowledge transfer. - THE ROLE - The role
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Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate
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biology, engineering, biophysics, computer science) and experience in 3D imaging of brain tissue, image segmentation, and handling large datasets. You are comfortable with machine learning and image
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programming such as Python, R, MATLAB, or other similar programs and experience in using simulation/optimisation models and advanced data handling techniques e.g. machine-learning techniques, statistics
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climate will warm and recover in a net-zero future. As part of this project, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques