59 digital-image-processing-phd-scholarship Postdoctoral positions at Duke University
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creativity, rigorous scholarship, and collaboration. You'll have opportunities to develop new skills, contribute to high-impact publications, and expand your professional growth while making meaningful
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. The Aleks Tata lab in the Department of Surgery, Duke University School of Medicine has an opening for postdoctoral researchers to study mechanisms in lung injury-repair. We seek to understand
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dyads, families, and service interactions across systems. Support data acquisition, integration, validation, quality assessment, governance, reporting, monitoring, and stewardship processes. 2. Lead the
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analysis and interpretation of multidimensional microscopy datasets, integrating image processing, spectroscopy, diffraction, and computational methods to extract meaningful scientific insights. 3) Lead the
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, neuroinflammation, tau and α-synuclein pathobiology, digital pathology/AI image analysis, and mouse models of neurodegeneration. Education: A recent Ph.D. (less than 2 years of postdoctoral experience is strongly
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acquire new technical expertise as needed. Participate in clinical research efforts involving retrieval, processing, and molecular analysis of patient-derived specimens from prospective clinical trials
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Communication & Scholarship Prepare manuscripts for publication in peer-reviewed journals. Present research findings at regional, national, and international scientific meetings. Contribute to grant proposals
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development of machine learning tools and their applications to medical imaging. Key Responsibilities: The Post Doctoral Associate will apply their technical skills toward the development, implementation, and
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to expand their scientific expertise while contributing to meaningful discoveries in vision science. What You’ll Bring Required Qualifications PhD or MD/PhD in a relevant scientific discipline. Strong
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) Evaluate the implications of these associations for extraction processes; and 3) Assess the critical mineral resource potential of unconventional wastes through geospatial and statistical analysis of supply