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techniques for integrating such solutions into modern SDV middleware. Responsibilities: Conduct research in runtime analysis and reconfiguration of in-vehicle TSN networks. Develop algorithms and prototypes
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of solvers for stochastic optimization problems, and test the methods on real-life data. As part of the PhD you will be following advanced courses to extend your skills, implement and test algorithms, and
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and time, with particular focus on migratory populations. Evolutionary genomics: determining adaptive variation within and among populations, including combining molecular and experimental analyses
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Job Description We invite applications for a fully funded PhD position focused on the development of advanced computer vision and machine learning algorithms for detection and identification
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-transpositions (plastys) and suture practices for surgical procedures. The specific PhD-project aims at developing efficient hyper elastic-based topology optimization algorithms that take into account skin
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, monocular depth estimation, and reinforcement learning. You will develop innovative algorithms that empower aerial robots to actively explore unknown, unstructured, and GNSS-denied environments while
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of Europe’s ‘green transition’ to clean energy. You will work on cutting-edge research tasks, with objectives including • new algorithms and strategies to improve autonomous Airborne Wind Energy (AWE) operation
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and automated catch registration to advance commercial fisheries. The team is developing fish detection and species identification algorithms, with the goal of implementing the software in
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and thermophysical properties. Furthermore, the group excels in development of efficient phase equilibrium calculation algorithms for compositional simulations. The project is supported by a robust
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candidates in any field of machine learning theory, algorithms and computation or in AI applications in e.g., the social, neuro, or natural sciences, are encouraged to apply. The position comes with a start