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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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Full time: 25 Hours per week Fixed term: 12 months We are looking for a candidate to join the University of Edinburgh to conduct research on Machine Learning, Reinforcement Learning, or LLM
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intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet
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on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring
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skills Desirable criteria Experience of atomistic modelling of ferroelectric materials Experience in development and application of machine learned potentials * Please note that this is a PhD level role
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experience in machine learning and image analysis for ultrasound images and video. The successful applicant will possess specialist experience conducting fieldwork, particularly in low-resource or rural
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of atomistic modelling of ferroelectric materials 2. Experience in development and application of machine learned potentials * Please note that this is a PhD level role but candidates who have submitted
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50 Faculty of Life Sciences Startdate: 01.10.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 17.11.2025 Reference no.: 4674 Explore and teach
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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climate scientists and artificial intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine