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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
Postdoctoral Research Associate to focus on computational neuroscience. Minimum Education and Experience Requirements PhD or MD. Required Qualifications, Competencies, and Experience Advanced knowledge
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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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will create a personalized training and development plan with the supervisor. Minimum Qualifications Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree
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exploring biophysical principles that regulate genomic processes. Applicants should have a PhD in molecular biophysics, biochemistry or a related discipline. The ability to work effectively in a team and
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the following documents to Rui Tang, PhD, Assistant Professor at ruit@wustl.edu . Cover letter expressing your interest and highlighting your relevant experience. Curriculum Vitae (CV) with a list of
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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Scale Tissue Atlas" project. -Duties include conducting research on image processing, image alignment, and instrument design and development for the funded projects. -This project will require expertise
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. It may also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be
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Responsibilities Specific responsibilities will include data acquisition (flow visualization, particle image velocimetry (PIV), pressure, acoustic, and high-speed video/kinematic measurements), analysis, and
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is 7/1/24. Qualifications Completed PhD or a foreign equivalent. The current project seeks to revolutionize the entire process from data to prediction with a paramount focus on reproducibility and