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power technologies and systems, energy-saving methods and efficiency optimization in hydraulic applications, digital fluid power systems including digital displacement pumps/motors, systems based on fast
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previously conducted research or have demonstrated knowledge within some of the following areas: classical and/or quantum data communication, error correction, communication algorithms, optimization algorithms
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, generative design, building performance optimization, digital design methods (e.g., predictive modeling, multi-agent systems and algorithmic techniques for architectural design), digital design epistemologies
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security guarantees. Topics include federated learning, secure computation, and robust optimization under adversarial threats. The candidate should have an MSc. in Machine Learning, Computer Science
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for integrating heterogeneous data from humans, robots, and environments into a unified control framework. You will create attention-based models that balance human input with environmental awareness to optimize