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-efficient, open-loop optimisation of fermentation control profiles, building on recent theoretical developments in optimal control theory, reinforcement learning and numerical methods as well as laboratory
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Job Description DTU Space invites applications for a three-year PhD position focused on the study of galaxies, galactic dynamics, stellar streams, dark matter, and numerical simulations. PhD
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begin with designing appropriate device geometry employing a broad spectrum of analytical, semi-analytical, and numerical techniques. Based on the results of the design process, a device will be
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information. The candidate will be responsible for developing detailed simulation models of both robots, sensors, and components to be assembled. In addition, the candidate should develop robust manipulation
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is expected to have a profound knowledge on most of the following topics: Robot control Deep Learning Medical imaging Preferably, the candidate has experience with: Robotic simulation tools Medical
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characterization techniques such as atomic-force microscopy or scanning electron microscopy. Experience with simulations of photonic nanostructures will also be highly valued. You should have a Ph.D. degree (or
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surgical robots across various surgical applications, using techniques such as advanced sensing, AI-based and reinforcement learning (RL)-based control, and soft continuum robot simulation. The starting date
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and reinforcement learning (RL)-based control, and soft continuum robot simulation. The starting date is expected to be February 15, 2025, or as soon as possible thereafter and will be agreed with