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mitochondrial quality leads to neurodegenerative diseases and impairs neuronal recovery. To approach these questions we use a combination of genetics, biochemistry, cell biology and imaging in a number of models
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will play a key role in automated wildlife identification and classification from trap camera images using cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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engines, energy systems, explosions, aerodynamics, fluid mechanics, signal and image processing, control systems, and robotics. The postdoctoral researcher will design and develop frugal artificial
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with archival best practices, including those related to research, processing, and/or digitization; basic familiarity with current approaches to digitization, image manipulation, file management, and/or
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at: https://www.directives.doe.gov/directives-documents/400-series/0486.1-BOrder-a/@@images/file
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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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policy. To apply for this position, please create a candidate profile at https://jobs.illinois.edu and upload your cover letter and resume by 6pm CST, April 27, 2026. Full consideration will be given
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Fagan Application Deadline: Applications accepted all year round Details Background: Clostridioides difficile is the leading cause of healthcare-associated infections and is notoriously difficult to treat
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experience with the following laboratory techniques: processing clinical samples, histology, cell culture, immunoassays, biomechanics, imaging, and data analysis preferred. Experience working with patient