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reservoirs. By embedding governing equations and boundary conditions directly into machine-learning models, the project aims to enable efficient exploration of high-dimensional parameter spaces without
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administration and organisation. We are looking for a/an Senior Scientist in Experimental Quantum Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours: 40 | Collective bargaining agreement
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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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We are seeking a talented and enthusiastic postdoctoral (or working towards a PhD) scientist with experience and a track record in machine learning, particularly for applications of deep learning
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EPSRC ReNU+ CDT PhD Studentship: Physics-informed machine learning for deep geothermal systems under uncertainty. Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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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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Apply and key information This project is funded by: Department for the Economy (DfE) Summary CNC machining delivers high precision but is costly, rigid, and limited in adaptability. Robotic
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and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine Learning as well as an ability to develop, build and test interactive
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(or working towards a PhD) scientist with experience and a track record in machine learning, particularly for applications of deep learning for medical imaging and/or molecular biomarker development, for a
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning