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Job Reference: 1069107 Full-time Continuing | Curtin Bentley Campus (Boorloo, Perth) Lead Transformation in Human Learning and Innovation Curtin University is a global leader in education, research
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About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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: human behavior analysis, supervised/unsupervised/self-supervised learning, deep learning. Research experience in multimodal human behavior analysis, affective computing, AI for Healthcare, and multimodal
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 month ago
equivalent doctorate (e.g., Sc.D., M.D.) Preferred Education Skills and Experience: Ph.D. in design-related discipline, specializing in deep learning and biometrics. A strong background with evidence of
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of Efficient Learning for computer vision Coding Skills: Familiar with any of the major deep learning libraries, including Pytorch We regret to inform that only shortlisted candidates will be notified. Hiring
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TEC. 2. OBJECTIVES: Collaborate with clinical partners in data collection and annotation Design and implement new deep learning solutions for the analysis of heart sound auscultation, electrocardiogram
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research track record, including high-impact publications, competitive grant success, and national/international presentations. Demonstrated deep knowledge and direct experience in proteomics techniques
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-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function
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who bring deep domain expertise in one or more of the following areas: Stem cells, organoids, tissue engineering, and/or 3D bioprinting Biomaterials for regenerative medicine and mechanobiology CRISPR
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experience in machine and/or deep learning applied to geospatial data. Demonstrated experience in the use of HPC and handling of very large datasets. Experience in software development and contribution