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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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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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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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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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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
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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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https://www.ntnu.edu/studies/phiv, see Section 6-1 of the PhD regulations for more information. You must have a relevant Master's degree in marine hydrodynamics, aerodynamics, fluid mechanics
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flexible fitting of mechanistic and statistical models to the data. Our current focus is on generating datasets of sufficient size and diversity to train machine learning models to accurately predict how