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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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above) grades. You have a strong background in deep learning. Previous experience with robotics, world models, reinforcement learning or other ML-based techniques for robot control is considered a plus
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to apply Website https://www.academictransfer.com/en/jobs/363306/phd-ai-based-cardiovascular-ima… Requirements Specific Requirements You are a motivated researcher with a strong technical background and a
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practical application of machine learning methods (especially deep learning) Publication of scientific results in renowned international journals and conferences Teaching of courses as well as planning and
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(especially related to applications of artificial intelligence), and real-world experiences so students not only accumulate knowledge but also develop the commitment and desire to apply what they learn in
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to engage with patients and real-world healthcare challenges.• Strong programming skills in Python; experience with deep learning frameworks such as PyTorch or TensorFlow is highly desirable.• Proven research
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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The laboratory of Dr. Ya-Chi Ho, MD, PhD at the Department of Microbial Pathogenesis (https://medicine.yale.edu/lab/yachiho/ ) is looking for a highly motivated postgraduate student with a strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and