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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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. The research tasks will include to develop machine-learning methods using experimental data provided by collaborating experimentalists. A central part of the work will be to identify and define the most relevant
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional team members to develop hypotheses, interpret data, and
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and vegetation development. This PhD project is part of a larger interdisciplinary research initiative aiming to enable a transition towards more data-driven and environmentally responsible maintenance
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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hypertension. This post creates a unique opportunity to generate high quality plasma proteomics data on a large patient cohort using mass spectrometry approaches. The postholder will then analyse these data
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, micro-CT, particle size analysis, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a
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for machine learning, autonomous, causal, and agentic intelligence, as well as interaction with humans, markets, and society at large. Our core mission is to educate and empower the next generation of