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of Engineering at The University of Texas at Arlington invites applications for a Postdoctoral Research Associate position in the area of biomedical engineering (imaging, bioinstrumentation or nanotechnology
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders. The ideal candidate will have a
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and learn independently and perform research with a high level of integrity. Well-organized and able to coordinate and interact with a team of other postdoctoral scholars, graduate students, research
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-Based Wildfire Smoke and Air Quality Monitoring; Deep Learning for Post-Wildfire Damage Assessment. PROFILE of the OFFICE OF POSTDOCTORAL AFFAIRS (OPA) The mission of the UNLV Office of Postdoctoral
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Preferred: Prior working experience with EHR data, machine learning, deep learning, imaging informatics, and large language models (LLM) is preferred. Prior working experience with popular ML packages, e.g
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) conferred by start date Demonstrated experience with imaging and/or video datasets Training and experience in machine learning, computer vision, and deep learning methods Excellent English language
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imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling
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appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Precision mapping of vector borne diseases using deep learning & high resolution remote sensing data Faculty in Stanford
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to appointment start date We welcome candidates with deep expertise in one or more relevant areas, and a strong desire to learn across disciplines: Computational Biology: Spatial/single-cell omics, bioinformatics