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the research project to design a mobile DC microgrid controller for military tactical applications. Develop control algorithms for dynamic master selection, coordinating BESS, PV, diesel generators, and other
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program development with topics like abstract data types, trees, graphs, sorting, searching, greedy algorithms, and basic AI classification techniques. Students will gain both theoretical understanding and
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responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real
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algorithms into UAV platforms. • Conduct field experiments and system validation for UAV swarm behaviors. • Prepare technical reports. Job Requirements: • Master in Electrical
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with strong experience in learning-based control and mobile manipulation. The successful candidate will work on algorithm development for contact-rich robotic manipulation, integrating perception
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. The incumbent will have the unique opportunity to work at the intersection of cutting-edge science and real-world application, developing groundbreaking algorithms and systems that mimic natural processes
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development of model predictive control algorithms for autonomous robots. Key Responsibilities: Development of model predictive control algorithms for autonomous robots Job Requirements: A Master degree in
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joint project related to policy-making in urban planning and design, focusing on developing a Multi-Criteria Decision-Making (MCDM) framework and tool. The work will involve integrating results from
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collection from both experimental and numerical sources, gathering relevant test and simulation data available globally, organizing the collected data to support model and control algorithm development and
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment