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algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems. The project focuses on the intersection of deep reinforcement learning
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. Job description The successful applicant will join our efforts to explore new types of nonthermal physics in strongly-correlated quantum systems. Such systems can display highly complex and unusual
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data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Postdoctoral Researcher for Complex Plant Data Integration
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systems. Such systems can display highly complex and unusual dynamics, and the successful applicant will contribute to a new research project on the dynamics of quantum many-body scars. The research will
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sustainable and resilient agricultural systems. The research team you will join is coordinating an international program that brings together leading scientists from around the world to investigate
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molecule) IR spectroscopy to follow in situ reactions leading to complex molecule formation on realistic dust grain analogue surfaces. Close collaboration with theoreticians, observers and the
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scanning tunneling microscopy (STM), temperature programmed desorption, and (single molecule) IR spectroscopy to follow in situ reactions leading to complex molecule formation on realistic dust grain
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and developing analytical approaches for studying complex PTM systems at proteome scale. We are currently expanding our activities at Aarhus University and are establishing an ambitious research