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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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impact on calcium signaling and cellular processes, including but not limited to neuronal function. You will be involved with teaching and supervising students following the problem based learning (PBL
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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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, 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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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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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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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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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
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electronic components including SiC/GaN based devices. The candidate will also have opportunity to work with industry related problems. Key Responsibilities Research & Learning: Develop expertise in advanced
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components including SiC/GaN based devices. The candidate will also have the opportunity to work with industry related problems. Key Responsibilities Research & Learning: Develop expertise in advanced control