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Field
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) computer vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial
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background in developmental neurobiology, cannabinoid pharmacology, and in vivo calcium imaging (fiber photometry). You should have experience or a strong desire to learn ex vivo electrophysiology
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the group of Dr. Eric Muir at the University of North Carolina at Chapel Hill in the Department of Radiology and the Biomedical Research Imaging Center. The successful candidate will develop and optimize
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between various imaging modalities and multi-omics during aging and development. • Implementing computationally intensive algorithms on high-performance computational clusters
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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. Effective communication skills and the ability to maintain detailed research records. Desirable Qualifications: Experience with single-molecule labeling and live-cell imaging/particle tracking. Programming
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commissioning of these prototype systems, co-develop improved suspension control schemes, and build hands-on expertise in suspension commissioning in preparation for an actual observation run. The work connects
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nanomaterials, with biological matter (proteins, cells, tissues) Experience with preclinical (rodent) in vivo handling procedures, including dosing (IP, SC), IVIS imaging and tissue collection (including personal
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-Doctoral (Level A) or Research Fellow (Level B) role. Please attach your curriculum vitae (including contact information for two referees) as part of the application process. Applications without cover
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community at UVA, with active collaborations across the UVA School of Medicine. The lab has full access to UVA's high-performance computing resources and core facilities supporting genomics and imaging