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, letters of recommendation, etc). What happens next? The assessment of potential candidates is made primarily based on academic results from bachelor degree and master degree studies. Short-listed applicants
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field
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Media (EDM), the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms, Implementations (RTG π³), the UBRA AI Center for Health Care , and the ZeMKI
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detection and classification algorithms using measured and/or simulated data, such as current pulses from cable faults (breakdown), partial discharges and external noise. In addition to being part of
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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multiscale analysis of the mass distribution, as well as that of the flow field structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have