33 machine-learning "https:" "https:" "https:" Fellowship positions in United Kingdom
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approaches. Machine Learning in Geotechnical Engineering: Utilising data-driven approaches to model and predict soil-structure interactions or other complex geotechnical problems. Reliability-Based
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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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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. Expertise in artificial intelligence and machine learning. Recent research experience in the development of first-principle wave models. Recent research experience in the development of numerical codes
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, b) computational modelling, or c) machine learning. This is a complex project managing longitudinal data from a range of sources. Therefore, thoroughness and attention to detail while managing
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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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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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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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