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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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Research Fellow-Cancer Research Grant Development Mgr,School of Medicine,University of Galway 011339
creativity, and is one of six global hubs for medical device development. Through our renowned research institutes and four Colleges, we engage in cutting-edge research that transcends borders, creating a
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About the position We are excited to invite applications for a Postdoctoral Researcher to join our team in developing cutting-edge computational tools for the design, synthesis, and characterization
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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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to treatment, population health monitoring, workforce development and leadership, policy, and advocacy. Background The Robotics, Autonomy and Machine Intelligence (RAMI) Group led by Prof Nabil Aouf is dedicated
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Astrophysics (CCA). The CCA offers FSRFs the opportunity for independent scientific software development and scientific research in areas that have strong synergy with the CCA or other centers at the Flatiron
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optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct computer programming to verify the efficiency of the designed solution algorithms Analyze data
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems