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is available in the exciting field of mathematics of deep learning, under the joint supervision of Prof. Alex Cloninger and Prof. Gal Mishne at UC San Diego. This NSF-funded research focuses on a
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Description Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in the Department of Radiology & Nuclear Medicine at the University
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among
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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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new MRI techniques for motion-robust imaging, real-time image processing, and/or deep learning. The work includes MRI pulse sequence design for various MRI techniques and technologies, algorithm and
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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NASA. The researcher will utilize multi-decadal satellite imagery and deep learning techniques to analyze temporal trends in urban structure and their impacts on microclimate, focusing on extreme heat
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. - Research Areas: Positions are focused around Deep Learning and Inverse Problem Regularization. Successful candidates will engage in diverse projects ranging from provincial to national levels, in
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simulations of PDEs, deep learning, neural networks. Our research interest: Our focus is on theoretical and computational biological physics, ranging from the study of molecules to cells. We strive to leverage