819 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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: Responsible for performing organic reactions in Dr. Sielecki’s lab within the Institute of Advancing Medical Innovation and the Department of Cancer Biology. Post-docs will learn methods appropriate
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renewable for a second year pending budgetary approval. In addition, the research support, the position offers the opportunity to teach one 3-credit course per academic year designed to help undergraduate
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biology, and evolution. Learn more about our interests, motivations and discoveries: https://sites.duke.edu/silverlab/ . Conduct independent research activities under the guidance of a faculty mentor in
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Qualifications Equipment Utilized Physical Demands and Work Environment Overview Candidates must be highly motivated, open to learning new techniques, and able to maintain excellent documentation of their results
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competencies Education You should have completed within the past five years or be close to completing a PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science
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implement new computational and statistical methods. Create, test, and use relevant computer code (R, Python, SQL or equivalent). Maintain, modify, and execute analytic machinery that results. Draft
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software ● Minimum 1-year experience in machine learning methods Knowledge, Skills and Abilities: ● Excellent communication skills (written and oral) using the English language
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] Subject Area: Statistics and Machine Learning Appl Deadline: 2025/12/01 11:59PM (posted 2025/09/04, listed until 2026/02/01) Position Description: Apply Position Description The Department of Mathematics
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment