61 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Duke University
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medical research needs Solid background in causal inference and survival analysis Experience with clinical trial research, machine learning, and high-dimensional statistics (desirable but not required
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to funding proposals Educational Requirements: PhD in Chemistry, biomaterials, chemical or biomedical engineering or related fields Experience Recommended (not all required): Demonstrated publication record
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regarding all facets of the Postdoctoral Appointee's research activities. Must hold a PhD Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity
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include teaching responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program, unless research training
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interested in applicants that have experience in one or more of the following areas: satellite remote sensing, energy balance modeling, and machine learning. In addition to scientific expertise, the successful
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developing and applying advanced statistical models, machine learning, and deep learning approaches. As such, we seek applicants with strong quantitative backgrounds in remote sensing and time series analysis
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recent Ph.D. in microbiology, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative
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Program, the Nancy Grace Roman Space Telescope, the Rubin Observatory LSST, and the Simons Observatory. The Duke Cosmology group currently consists of about ten PhD students and seven postdocs or research
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Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency. 1. A candidate may also be appointed to a postdoctoral
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such as the Integrated Toxicology and Environmental Health Program, the Superfund Research Center, and the Center for the Environmental Implications of Nanotechnology. TERM: 1 year, with the possibility