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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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maturity and business readiness. In this position, you will work in close collaboration with companies in the sectors of metal products & components, mechanical & electro-mechanical products, electronics
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imaging-driven quantitative Mass Spectrometry-based omics methods, both at bulk population and single-cell levels, for this project. You will work closely with experts in cellular signalling, proteomics
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opportunity to contribute to cutting-edge research in the development of clinical trials, self-management science, acute/chronic disease management and pain mechanisms and methods under the mentorship
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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project “Spin-orbit coupling and dimensionality at the heart of quantum magnetism of heavy transition metal oxides”. The project is jointly funded between ISIS Facility (led by Dr Devashibhai Adroja) and
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transition metal complexes, donor-acceptor pairs, and hybrid molecular-material interfaces. By designing and deploying state-of-the-art ultrafast nonlinear optical spectroscopy techniques—such as transient
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dimensions and will examine family and family life as fundamental to the waging and experience of war. The project is interdisciplinary and will utilize mixed methods. The project will have three contemporary
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About Us The Faculty of Life Sciences & Medicine is one of the largest and most successful centres for research and education in the UK. The Faculty was created as a result of the merger of elements