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models and data-driven approaches for adaptive, real-time operation of complex energy systems. Applications such as drying processes serve as test cases, but the goal is to establish methodologies
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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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computational modelling. You have experience with Machine Learning and data analysis and are motivated to apply these skills to complex materials and production systems. You are familiar with polymer materials
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Imagine a world where food production is in harmony with natural processes, farmers nurture healthy soils, and biodiversity thrives. In contrast, current monoculture farming systems undermine this
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thereafter).The duration of the position is three years. Job Decription Species interact in complex biological networks e.g. food webs, forming the foundation of natural ecosystems. Yet, we lack the
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develop new strategic roles to become active platforms for collaboration across logistics, energy systems, industrial development, and regional transformation. Ports have traditionally served as
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DTU Tenure Track Assistant Professor in Surface Physics and Catalysis for Sustainable Energy Solu...
infrastructures that enables research into the transition toward a non-fossil energy society. The position focuses on the conception, design, and implementation of advanced UHV systems for atomic-scale
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geometrically complex environments, and safe motion planning within centimetres of critical infrastructure. Concretely, the work will include the following: State estimation and localisation in GNSS-denied
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contribute to new strategies for controlling protein function in complex biological environments. The research project: PROTÆCT This postdoc position is part of the Villum Foundation funded project