404 machine-learning-"https:" "https:" "https:" "https:" "https:" Postdoctoral research jobs in United States
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly
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the lab. Hiring rate for this position is $64,723. To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/30571 Qualified candidates should submit a short cover letter
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research and experimental data in accordance with established protocols. Assist in statistical and comparative analysis of experimental data using appropriate computer software. Contribute to the preparation
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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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: 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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Laboratory (CIRL) – http://cirl.memphis.edu – in the Department of Electrical and Computer Engineering, The University of Memphis. The postdoctoral researcher will have the opportunity to work with Dr
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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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. Contribute to the development of research grants for funding of lab training and research. MINIMUM QUALIFICATIONS PhD in neuroscience, neurobiology, machine learning, biomedical engineering, or related field
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. Candidates with expertise in climate science, hydrology, earth and planetary science, and physically-based or machine-learning/AI-based climate modeling (e.g. hydrometeorological and/or atmospheric processes
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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact