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Field
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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meet the requirements for admission to the faculty's doctoral programme in Engineering Cybernetics . Strong programming skills, in particular Python, and practical experience with modern machine learning
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access to research vehicles and advanced radar prototypes
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by a more experienced theoretical postdoc. In the second phase of the project, work will move towards current-driven dynamics of the nanosized textures, the exploration of topological excitations, and
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postdocs in the SteeleLab in the Quantum Nanoscience Department in Delft. You will meet regularly with your supervisors and other team members, and also be encouraged to develop and explore your own ideas
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning
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also include generative or predictive modeling of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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. As a PhD researcher, you will unravel the atomic-scale mechanisms of hydrogen embrittlement in compositionally complex recycled steels, using density functional theory and machine-learned interatomic