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socially just energy supply system based on renewable energies. We contribute to this with our research focus on energy supply, energy distribution, energy storage and energy use. Through outstanding
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you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
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socially just energy supply system based on renewable energies. We contribute to this with our research focus on energy supply, energy distribution, energy storage and energy use. Through outstanding
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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the distribution of mechanical loads in the wind farm, thus also extending the lifetime of the wind farm. Your PhD project is integrated into the Living Lab 70 GW Offshore Wind, which researches crucial aspects
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identifying climate-resilient restoration sites in the Baltic Sea. The project integrates regional climate modeling, AI-driven simulations, and biogeochemical modeling to predict seagrass distribution under
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tasks: Computationally design and simulate neuromorphic hardware including novel materials, devices and circuits. Implement bio-inspired learning algorithms on said hardware. Collaborate with
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to their spin properties. What you will do You will program the connection of quantum experiments to an existing HPC system for the external execution of quantum algorithms. You will develop an efficient user
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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appearance changes due to weather and season these algorithms can lead to wrong associations and degraded performances. The classification and segmentation of the point cloud information can be a major