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Field
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generation of social, computer-based, and cyber-physical systems that make a substantial contribution to the welfare of our society, for example, via embodied intelligent systems that are tailored to users
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and non-university research and development institutions are working together in a unique collaboration and a state-of-the-art environment to develop the data-based technologies and smart applications
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challenges of our time. Be part of change As part of the interdisciplinary “Machine Learning Enhanced Sensor Systems” team, you will work on and develop data-driven solutions for intelligent sensor technology
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the VIOLET research framework Work closely with clinicians and data scientists to ensure the developed systems meet clinical needs and are validated against real-world scenarios Mentor and supervise PhD
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macromolecular dynamics with machine learning, statistical mechanics, molecular simulations, and experimental data. The joint project “FAIME – Flexible and Efficient AI-driven Molecular Simulation Engine” is part
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or more. Selection Applications are reviewed and selected by a DAAD selection committee. The approval of the K.C. Wong Education Foundation is then required. Further information The DAAD will not consider
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pro-rata for different periods. Application Papers You will find all application forms and further information on the application procedure here . Application Deadline Applicable deadlines will be
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Robot Learning (ID: TUEILSY-POSTDOC20251219-RL) Robots that learn from data promise greater autonomy and performance, but their deployment in the real world hinges on the ability to guarantee safety
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imaging systems and ensure the optimal deployment and networking of sensors to efficiently process and analyze the resulting data streams. In this way, we support people in decision-making, process
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. As part of our project with the start-up TwinCloud, we are looking for a Student