42 machine-learning positions at Delft University of Technology (TU Delft) in Netherlands
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share the ambition to be the world’s top scientists in the field of AI and machine learning, and encourage you to spar with us. Fostering a welcoming and collaborative atmosphere, we will give you all
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following aspects will help you stand out: Knowledge of data-driven control algorithms, biomechanical modelling, system identification, machine learning, control theory. Prior experimental experience on human
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Job related to staff position within a Research Infrastructure? No Offer Description You will conduct both theoretical and empirical research at the intersection of logic, optimization, machine learning
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-box nature of machine learning models, you will bring clarity and predictability to your models. Trust will be earned as you evaluate the robustness of your models in different scenarios, identifying
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-informed machine learning. You have excellent spoken and written English language skills*, and demonstrable collaborative, communicative and organizational competences. Affinity with inverse problems
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research seeks to pioneer intelligent security analytics for a zero-trust 6G infrastructure. This includes developing machine-learning models adept at detecting and neutralising threats and cyber-attacks
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, focusing on research in the areas of machine perception, motion planning and control, machine learning, automatic control and physical interaction of intelligent machines with humans. We combine fundamental
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. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty quantification), experimental device testing, cardiovascular (patho)physiology, and strong and
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of life. Our mission is to bring robotic solutions to human-inhabited environments, focusing on research in the areas of machine perception, motion planning and control, machine learning, automatic control
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methodologies (e.g. physics embedded machine learning) for sparse 2D Tx-Rx topologies integrated with DoA estimation. Verify theoretical results via simulations and experiments. Contribute to the scientific