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purchasing policies, strategic sourcing goals, and operational standards. Success in this role requires both technical expertise and deep institutional knowledge of UCSF's supply chain processes, policies, and
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learning libraries (e.g., PyTorch) Desirable criteria Research experience in one or more of the following areas: tactile sensing, robot grasping and manipulation, robot control, computer vision, deep
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payment sites. Secure classrooms and other spaces for training programs. Employees at St. Kate's feel a deep connection to the University's Mission and Vision, and they live their values at work. Benefits
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mechanisms available in multi-parametric MRI, we aim to establish deep learning models that predict biomarkers of diseases progression and response to therapies, with applications in brain tumours and neuro
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Government, and non-profit laboratories, especially APL, is preferred. - A strong background in Artificial Intelligence (AI) or a related field, with a deep understanding of current technologies, trends, and
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the composition and functioning of microbial communities in environments ranging from the deep sea to large lake systems. Within this department a subgroup of organic geochemists is developing novel (analytical
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perception systems, using deep learning and simulation-to-real domain adaptation techniques. You will work with a multidisciplinary team, contributing to fundamental and applied research. Your role will
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of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large
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, and artificial intelligence. Visual understanding has made remarkable progress due to advances in deep learning technologies. Furthermore, technologies that combine videos/images with natural
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independently and collaboratively Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous Effective communication skills and an interest in contributing to a highly international