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Field
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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development of transparent, closed-loop control system for individualized diuretic closing including the validation and advancement of machine-learning and control algorithms, building production-oriented
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learning based optimization algorithms, human and AI coordination in best decision making for urban transportation related problems. The role will focus on developing generic frameworks and innovative
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to minimize algorithmic bias. Develop expertise in evaluating AI devices that can adapt and learn post-deployment, including understanding evolving algorithms and creating methodologies to assess algorithm
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Fellow to conduct cutting-edge research in AI-enabled modelling and design of microwave and RF devices. The successful candidate will develop advanced physics-assisted modelling techniques to accelerate
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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 to build and
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is interested in understanding the neural and algorithmic basis of sensory-guided behaviors in terrestrial animals. We have developed behavioral tasks in mice using stimuli and situations
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collaborative research projects, develop novel computational algorithms, and contribute to high-quality publication and grant-related activities. The position offers opportunities to work in a dynamic research
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systems, Wireless Power transfer, Thermal/colling management, and Battery Management Systems. • Develop digital twins of the detailed electrical power system based on the concept design in real-time
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) will contribute to a two-year applied research project funded by the BCA, focusing on the development of a power grid interactive building or cluster of buildings. The role involves designing and