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. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including
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. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address
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Department: College of Science Classification: Post Doc 12 month Job Category: Postdoctoral Faculty Job Type: Full-Time Work Schedule: Full-time (1.0 FTE, 40 hrs/wk) Location: Fairfax, VA Workplace
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control strategies. Develop and implement advanced control algorithms for real-time operation and performance enhancement of power electronic converters and transformer-based solutions. Perform hardware-in
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develop algorithms to identify and predict SRL subprocesses from multimodal learning data (e.g., EEG/fNIRS, eye-tracking, and think-aloud protocols); • Analyze large-scale learning analytics data
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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Fellow in Autonomous Systems and Control to design and implement efficient, performance‑guaranteed distributed control approaches, leveraging cutting‑edge learning algorithms and AI strategies
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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model checkers; proofs of safety and/or security properties; programming languages and/or type systems; concurrent and/or distributed algorithms; and related topics. The successful applicant will work in
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno