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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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, evaluating, and fine-tuning machine learning models (e.g. deep neural networks) to segment underwater scenes and classify anomalies. The work will explore the use of virtual environments and synthetic datasets
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about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its
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microenvironments, molecular biology, and with experience in, or interest in learning, basic computational biology methods. Candidates must be able to perform as part of a team as well as independently, and must have
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modeling of dynamic systems. Experience with machine learning or AI methods applied to robotics (e.g. reinforcement learning for control, or data-driven modeling) is a plus, especially if applied in
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, fluid-structure interaction) Desire to develop interdisciplinary expertise across hydrodynamics and structural mechanics. Experience with or willingness to learn: Programming (e.g. C++, Python, Matlab
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medicine. We offer a lively, engaged and innovative learning and study environment, which is closely integrated in the research environment. Our department has unique and advanced animal experimental
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science, culture, and learning. The Centre benefits from SDU’s strong industry connections in Southern Denmark and Northern Germany, including collaborations with leading companies in sectors like e
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to lifelong learning students. We have about 300 dedicated employees. Read more about us at www.energy.dtu.dk . Technology for people DTU develops technology for people. With our international elite research
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing