458 machine-learning "https:" "https:" "https:" "https:" Postdoctoral research jobs in United States
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provision of clinical services. Multicultural Competence CAPS clinical/administrative staff are committed to for all students and advance CAPS¿ overall mission of facilitating students¿ personal learning
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, Physics, Engineering, or a related field, earned within the past six years Experience with AI and machine learning Excellent written and spoken communication skills Demonstrated ability to produce high
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: Geant4/TOPAS/GATE, etc.) Measurements – Treatment planning System. Prior Knowledge in Machine Learning algorithm is a plus. Supervisory Responsibilities No Required operation of university owned vehicles
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working on their own research and connecting to colleagues across the university. Depending on interests and feasibility, they may be able to teach and/or engage in off-campus fieldwork with Professor
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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engineering, materials science and engineering, or computer science and engineering. The postdoctoral fellow is expected to actively work with more than one CQISE faculty member at OSU to strengthen
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field. Strong programming skills (e.g., Python) for scientific computing and simulation. Familiarity with machine learning (ML) techniques for optimizing models or analyzing complex datasets. Experience
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retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ . Duke is an Equal Opportunity Employer committed
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] Subject Areas: Physics / Hard Condensed Matter Theory , Machine Learning , Material Science , Physics , Quantum Information Science , Soft Condensed Matter Theory , theoretical condensed matter physics
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data management sufficient to create, transform and integrate data in a variety of resolutions and formats. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and