466 machine-learning "https:" "https:" "https:" Postdoctoral positions in United States
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electromagnetic (EM) theory/modeling, at the Electrical and Computer Engineering Department, and in collaboration with the Applied Mathematics Department, Santa Clara University. This is an in-person position
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morphology (e.g., geometric morphometrics, machine learning), and phylogenetic comparative approaches. We have: • An engaging, supportive, and collaborative research environment. • Opportunities
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from varied sources, and machine learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with
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(dark matter, baryogenesis) and machine learning applications in these topics. The University of Oregon also has an experimental high energy physics group involved in the ATLAS experiment at the LHC and
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residence, to conduct research in Duke's library and archival collections, to participate actively in the intellectual life of the university, to teach up to 2 courses per year, and to give a public lecture
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing
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applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention to detail and follow-up skills Strong customer service skills and phone and e-mail etiquette USG Core Values
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opportunity to align with the most relevant academic department in the College of Architecture, Art, and Planning and teach one course per year subject to department needs. The Postdoctoral Associate will be a
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operations in the following areas: Soil & Groundwater; Deactivation & Decommissioning; Tank Waste; Robotics; Machine Learning; Artificial Intelligence; Cybersecurity; and Advanced Manufacturing. Are you
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
for extension based on mutual interest. We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with