2,291 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" PhD scholarships
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The Machine Learning for Integrative Genomics team (https
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Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech
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to staff position within a Research Infrastructure? No Offer Description PhD Position in Physics-Informed Machine Learning for Cardiac Magnetic Resonance The CMR Zurich group at the Institute