2,377 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Postdoctoral positions in United States
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 21 days ago
machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong programming skills, including TensorFlow and/or
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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
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position. Appointment Start Date: Ideally on or before July 1, 2026 Group or Departmental Website: https://med.stanford.edu/buckwalter-lab.html (link is external) https://med.stanford.edu/neurology/divisions
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Postdoctoral Associate to begin July 1, 2026. The one-year term position is renewable for an additional year based on performance and is part of Cornell’s Active Learning Initiative . This initiative supports
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eligible for, including health insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https
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: The appointment will be for one year. Appointment Start Date: 01/15/2026 or once the position is filled Group or Departmental Website: https://woods.stanford.edu/ (link is external) https://fieldlab.stanford.edu
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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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Associate as part of Cornell’s Active Learning Initiative (https://teaching.cornell.edu/active-learning-initiative-0) for the AYs 2026 – 2028. We invite applications from candidates with a specialization in
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patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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) Cleaning and managing large datasets from administrative data sources or online learning platforms Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML) Learning