72 software-engineering-model-driven-engineering-phd-position Postdoctoral positions at Duke University
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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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Duke University, Biomedical Engineering Position ID: Duke -BME -DUKENIKIFOROV [#29987] Position Title: Position Location: Durham, North Carolina 27708, United States of America [map ] Subject Area
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Health Program Program Type: Postdoctoral Location: Durham, North Carolina 27708, United States of America [map ] Subject Areas: Biology Mechanical Engineering Public Health Biomedical Engineering
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Location: Durham, North Carolina 27708, United States of America Subject Area: Biomedical Engineering / Genetics Appl Deadline: (offers accepted posted 2024/10/24, listed until 2025/04/24) Position
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and health, either with a background in population health analyses or laboratory research experience in molecular toxicology assays based on the zebrafish model. PROJECTED START DATE: The position is
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independent research activities under the guidance of a faculty mentor in preparation for a full-time academic or research career. Work Performed DEFINITION: The Postdoctoral Appointee holds a PhD or equivalent
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Duke University, Biomedical Engineering Position ID: Duke -BME -DUKEVENTURELLI5 [#29741] Position Title: Position Location: Durham, North Carolina 27708, United States of America [map
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. Postdoctoral Research Position A postdoctoral research position is available at Dr. Park’s laboratory in the Department of Pathology at Duke University Medical Center, Durham, North Carolina. Dr. Park’s
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Duke University, Biomedical Engineering Position ID: Duke -BME -DUKESONG1 [#29728] Position Title: Position Location: Durham, North Carolina 27708, United States of America [map ] Subject Area
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directions that can seed future independent positions. Work Performed Depending on candidate interests and expertise, projects may involve: Analysis of global dietary patterns using genomic approaches