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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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candidate will work on algorithm development for contact-rich robotic manipulation, integrating perception, planning, and control within a real-world robotic system. Job Responsibilities： Develop, implement
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, focusing on the development of a mobile DC microgrid for military tactical applications. The role involves designing and implementing advanced control algorithms to coordinate multiple energy sources
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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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edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is
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inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference
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cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap
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(OpelRT or Typhoon), electrical system design for better efficiency and system resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge
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timely completion of all project deliverables. Implement and enhance GeoTOPSIS/VectorMCDA algorithms within QGIS using Python or equivalent programming frameworks. Develop a user-friendly interface (QGIS
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of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep