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Field
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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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data-driven learning and which should remain within structured optimization. In line with AID’s research areas, the project will emphasize knowledge embedding, uncertainty representation, risk-aware
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selection criteria Knowledge of sensors and measurement techniques Experience from the industry providing sails for merchant ships Experience with Computational Fluid Mechanics Knowledge of machine learning
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unpredictability such as entropy. You will also investigate the robustness of these mechanisms to disturbances and assess whether transmission patterns can be learned from external observations. This position is
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to contribute to high-tech applications, state-of-the-art modelling or experimentation of advanced sustainable materials across the scales? We are looking for outstanding and enthusiastic PhD candidates, with a
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for recruitment positions for general criteria for the position. Preferred selection criteria Good oral and written presentation skills in Norwegian/Scandinavian equivalent level or acquire them during the course
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as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the project Can AI interpret graphs like a human materials scientist
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in one or more of the following research areas is desirable: geometric numerical integration, structure preserving deep learning, stochastic differential equations, generative AI, numerical
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skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing to solutions that really make a
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independently. Good communication skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing