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Challenge: Solve computational bottlenecks in the modelling of mechanics of metallic systems. Change: Develop new physics-informed machine learning algorithms and predictive models. Impact: Enable
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Explore and develop scalable machine learning methods for aerospace structures' design and manufacturing This postdoctoral research aims at exploring statistical methods that enable the data-driven
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Are you fascinated by the intersection of turbulence modelling, machine learning and laser satellite communications? If so, we welcome you to apply for this exciting opportunity. Laser satellite
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-driven control algorithms, biomechanical modelling, system identification, machine learning, control theory. Prior experimental experience on human body dynamics and motion comfort. A strong academit track
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related field. Proficiency with machine learning methods and corresponding software packages is a plus. Experience with ultrasonic welding is a plus. Fluency in English and proven academic writing skills
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a PhD in aerospace engineering, applied mathematics, mechanical engineering or other related fields. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and
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participants, machine learning. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (based on scale 10: €3.226,00 - €5.090,00). Depending on your knowledge and
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been well understood to this date, primarily due to the missing link between data analytics techniques in machine learning and the underlying physics of dynamical systems. The goal of this project is to
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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 research
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. The data acquired 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