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PhD student in generative modeling for data-efficient machine learning Norrkoping Reference number LiU-2026-02831 We are now looking for a PhD student in machine learning with a focus on generative
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PhD student focusing on Machine Learning of Geometric Representations at ISY Linkoping Reference number LiU-2026-03853 We have the power of over 50,000 students and co-workers. Students who provide
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PhD in Materials Science Norrkoping Reference number LiU-2026-03852 Join us in developing machine-learning accelerated simulation methods to understand and optimize interfaces in hybrid organic
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Join us in developing next-generation, machine-learning accelerated computational models to understand and predict coupled ionic and electronic transport in organic materials for sustainable energy
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and apply AI and machine-learning methods to infer interaction networks from acoustic co-occurrence and activity patterns, and analyse their structural properties to link topology to response diversity
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deep learning, machine learning, or large-scale omics data analysis. A high level of self-motivation and independence, good problem-solving skills, and the ability to work collaboratively in an
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involve developing and applying high-fidelity CFD models of turbulent flows in hydraulic turbines, integrating machine learning and deep reinforcement learning algorithms with numerical simulations
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involve writing and running code to process sequencing data on a computer server, applying statistical models and machine learning algorithms, and performing downstream data analysis, including
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forensic samples using high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you
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initiatives. Cases will include projects involving Swedish companies and projects led by actors from other countries. This approach will support international comparison and learning while providing access to