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, and formulation of clinical study design, image processing, machine learning, and statistical analyses to illuminate specific research questions. Among the machine learning techniques, deep learning
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- “Towards digital biomanufacturing – developing physics-informed machine learning framework for the advanced multi-modular 3D bioprinting system”. Qualifications Applicants should have: (a) a doctoral
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successful candidate, you will: This project with Dr. Nagarajan Vaidehi involves developing and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in
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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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, United States of America [map ] Subject Area: Computer Science / Artificial intelligence and machine learning Appl Deadline: 2025/11/20 11:59PM (posted 2025/10/23) Position Description: Apply Position Description
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at the University of Adelaide, contributing to cutting-edge research in computer vision and machine learning for space applications. This role focuses on advancing machine learning and computer vision research, with
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wide range of research, including quantum information and simulation, artificial Intelligence and machine Learning, and physics within and beyond the Standard Model at current and future colliders. The
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics
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research experience to include: Experience developing novel deep learning methodologies (e.g. transformer models, Convolutional Neural Networks, Auto-encoder models, or LSTM networks). Demonstrable ability