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Field
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command of qualitative research methodologies and research design. You are an independent and reflective thinker, able to engage with different theories and perspectives and reflect on your own
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
command of written and spoken English Basic programming skills and basic knowledge in the fields of machine learning and material simulations (i.e., quantum chemistry, density-functional theory, machine
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Are you passionate about mathematical systems and control theory? Are you interested in working with next generation high-tech systems? The main challenge lies in the reliable operation of
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command of qualitative research methodologies and research design. You are an independent and reflective thinker, able to engage with different theories and perspectives and reflect on your own
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discrete-event systems, supervisory control theory, and formal methods to apply for the PhD position within the Supervisory Control group (see Group Supervisory Control ), which is part of the Control
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of the following areas: Robotics Control theory Deep Learning & Machine learning Modelling and control of soft/continuum robots Experience with embedded systems programming (Preferably) with a strong background in
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control and reinforcement learning supported by an edge-cloud-based wireless communication environment. The doctoral student will work on data-driven theory and method development in simulation environments