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-Based Wildfire Smoke and Air Quality Monitoring; Deep Learning for Post-Wildfire Damage Assessment. PROFILE of the OFFICE OF POSTDOCTORAL AFFAIRS (OPA) The mission of the UNLV Office of Postdoctoral
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Regenerative Medicine Postdoc Appointment Term: 1 year initially and renewable. Appointment Start Date: Immediately available but flexible Group or Departmental Website: http://www.liwanglab.org (link is
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on the circular economy. This role requires deep expertise in advanced survey methodologies, experimental design, and statistical modeling. The ideal candidate has a strong research publication record and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
, robustness, calibration, bias/fairness, and/or adversarial stress-testing. - Solid programming and ML/NLP engineering skills in Python and ideally modern deep-learning stacks (e.g., PyTorch/JAX, HuggingFace
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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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O’Shea (Woods Institute) Stanford Departments and Centers: Woods Institute Postdoc Appointment Term: Initial appointment is one year, with a second year contingent on funding, results, and mutual agreement
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SPECIFICS Postdoctoral Scholar – Public Health Sciences Postdoctoral Scholar of Machine Learning and Statistical Genomics Description: The Department of Public Health Sciences is seeking postdoc scholars
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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of the appointment. Demonstrated experience with deep learning methods or sophisticated mathematical frameworks applied to large-scale or scientific datasets. Experience working with observational seismology data (e.g