65 technology-"https:"-"https:"-"https:"-"https:"-"SUNY" Postdoctoral positions at Duke University
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for postdoctoral fellows. We are seeking highly motivated candidates to join our research program in regeneration genomics. Our laboratory develops and applies cutting-edge genomics and proteomics technologies
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will help advance novel imaging technologies, analyze complex medical imaging data, and contribute to research that has the potential to improve patient outcomes worldwide. What You'll Do: Conduct
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forefront of ophthalmic research, where advanced imaging technologies, machine learning, and clinical expertise come together to solve complex healthcare challenges. In this role, you will support the
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, technologies, and commercial reagents, sharing knowledge with team members. Contribute to the development and implementation of new research procedures and innovative experimental approaches. Collaborate
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the development of new imaging protocols. Minimum Requirements: Ph.D. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) in biomedical engineering, electrical or computer engineering, medical physics
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leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve how caregiver-child interactions and
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technologies to study the behavior of tissues at single cell resolution. We offer an inspiring intellectual, collaborative, and multidisciplinary research environment to support your career goals and provide
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this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have
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diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all
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Academic credentials: PhD in ecology, biology, statistics, computer science or engineering, or oceanography with a strong quantitative analysis background, particularly in species distribution modeling