42 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" Fellowship positions in United Kingdom
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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
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establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD
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for MND which could be translated into the clinic. The idea is to use cutting edge machine learning to create clinically actionable predictions such as the time from diagnosis to requirement for a