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Field
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diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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scientists at six institutions in the Ruhr area covering experimental chemistry, theory and chemical engineering investigate how solvents are involved in the control, mediation and regulation of chemical
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Your Job: Reinforcement Learning (RL) is a versatile and powerful tool for control, but often data-inefficient, requiring numerous updates and non-local information such as replay buffers and batch
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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with background in biology and medicine, as well as mathematical, computational, and engineering disciplines are also encouraged to apply. They should be enthusiastic about developing new methods in
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van der Waals materials; ready-to-use and up-to-date knowledge of spectroscopy and microscopy; experience with strain engineering and hybrid heterostructures; excellent command of English language. TUD
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sustainable bioeconomy. The four PhD projects are: Your Profile: Master’s degree (or equivalent) in computer science, applied mathematics, physics, engineering, biology, plant and agrosphere sciences
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
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/casa-sdl-dbe Your Profile: Master’s degree (or equivalent) in computer science, applied mathematics, physics, engineering, biology, plant and agrosphere sciences, or another relevant natural science