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Cohesion grant, a internal TUD scheme to support tenure trackers. The Postdoc will be hosted by the Intelligent Vehicles Section. The section consists of three groups (Machine Perception, Human Factors and
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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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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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. 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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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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, model-based and data-driven fault detection and identification, moving horizon estimation, convex optimization, randomized algorithms, stochastic programming, machine learning. In addition, excellent
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systems to handle complex deformations. Candidates should have a robust background in control theory, nonlinear dynamics, or machine learning as applied to robotics. Publications in these fields
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opportunity to learn a lot and contribute to the next generation of machines that will improve the assembly speed and reduce the environmental impact of the production of hundreds of billions of future chips
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with your chip(s) will be analyzed with machine-learning algorithms. You will collaborate with researchers and companies of various disciplines like chemistry, embedded systems, software, signal
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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