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: A PhD in Physics, Computer Science, Mathematics, Machine Learning or relevant fields. Strong publication record in top conferences/journals, such as Nature Physics, Nature Communications, PRL, T-PAMI
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing can be
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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and thermal-aware design techniques for embedded systems. Contribute to research outputs and support timely completion of project milestones. Job Requirements: Preferably PhD in Computer Engineering
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, Computer Science, or related field, with strong background in machine learning Publications in top-tier journals and/or conference presentations as first author Proficiency in AI programming languages
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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decision-making and research findings. Qualifications & Competencies: Minimally a PhD degree in Artificial Intelligence, Computer Science, Optimization, or a related field. Strong foundation in multi-agent
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machine learning applications will serve you well as you liaise with project researchers, collaborating companies, clinicians and end-users in the User Group, to ensure overall COG-MHEAR programme goals
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community