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of output from global climate models (CMIP-class models) as well as Integrated Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer
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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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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 position
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drivers and other disease vulnerabilities. Educational Requirements: Doctorate (MD, PhD, VMD, or DDS) in area directly related to field of research specialization required. A candidate who has experience
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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 position
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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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manuscripts and preparing talks/presentations on the findings. We are interested in outstanding candidates who have a PhD in in organizational behavior or social psychology, with strong experimental research
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and non-invasive neurostimulation. The strong interdisciplinary and collaborative environment at Duke is ideal for our multi-scale modeling research efforts. An earned PhD and previous experience in
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outside Duke University. Preferred qualifications: PhD (completed in the last 1-5 years or PhD candidate) in a quantitative discipline, including Computational Biology, Bioinformatics, Computer Science
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and dry forest-grassland ecosystems. We seek candidates with experience in integrating multi-source remote sensing with field sampling to study vegetation dynamics (e.g., phenology) and its response