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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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. Proficiency in programming languages like C and Python, as well as deep learning frameworks such as PyTorch and TensorFlow. Knowledge in imaging and computing device and equipment. Strong communication
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equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine
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maritime transport, marine technology, computer science, or a related field; Excellent programming skills, such as Python, Matlab, C++, or other computer languages; A record of publications in reputable peer
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Responsibilities: Conduct advanced research in secure multi-party computation with applications to privacy-preserving machine learning. Develop scalable multi-party computation frameworks to enhance existing
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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
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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
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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
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low