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The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices. The successful applicant will conduct
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for Sustainable Energy, researchers from academia and industry develop, implement and evaluate new deep reinforcement learning methodology to solve sustainable energy challenges. Key responsibilities The lab is
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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Humanities and Law are organized into different Units: Entrepreneurship, Ethics and Leadership Governance, Culture and Learning CBS Law Faculty within these units have research backgrounds in various areas
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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Job Description We are seeking a senior researcher with a strong scientific background, deep passion for innovation, proven leadership experience, and a collaborative mindset to lead a research
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We are seeking a senior researcher with a strong scientific background, deep passion for innovation, proven leadership experience, and a collaborative mindset to lead a research group dedicated to
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partner in an exciting 5-year collaborative program. We are currently seeking applicants for three PhD projects as listed below. The successful candidates will be based in either NIBRT or UCD and will also
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as