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Training Program. This position will be funded by our NIDDK T32. Eligibility: U.S. citizenship or permanent residency required PhD applicants must have been awarded their degree or anticipated prior to June
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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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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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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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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
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neural stimulation and/or computational neural modeling are required as are excellent communication skills. The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates
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analysis tools Experience in machining learning methods in omics analysis Experience with high-performance computing and cloud-based analysis platform Previous experience in grant writing and manuscript
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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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the individual's research skills for his/her primary benefit. This multidisciplinary program is focused on developing the next generation of researchers in the field of aging, and competitive candidates will
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collaborative environment at Duke is ideal for our multi-scale modeling research efforts. An earned PhD and previous experience in computational neurostimulation modeling are required as are excellent