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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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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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programming Creating their own mechanical designs, implement and test them accordingly, Implementation of control algorithms on physical experiments. In addition, the candidates are expected to contribute with
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed
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, storage and demand. YOUR TASKS You will develop mathematical models and metaheuristic algorithms for complex optimization problems in the context described above, see e.g., https://arxiv.org/abs/2503.01325