61 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Duke University
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, variations in concentrations of atmospheric pollutants, and shifts in direct application of nitrogen to ecosystems. The candidate must have a PhD degree in a related field, be fluent in computer programming
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of Business at Duke University will have an opening for a postdoctoral position beginning October 1, 2025, to work on projects related to the psychology of successful military veteran transitions
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theory, multi-objective optimization and machine learning. The specific project aims to understand the multiscale interactions shaping human gut bacteria and human gut pathogens. The project will combine
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identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on
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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
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· Possess the knowledge of basic research integrity, values of ownership of a research project, and follow timelines to achieve deliverables Requirements: · MD, MBBS, PhD (with clinical research experience
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27710, United States of America [map ] Subject Areas: Data Science / Machine Learning Statistics / Statistics Biostatistics / Biostatistics and Data Science Appl Deadline: none (posted 2025/02/12
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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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. TERM: 1 year, with the possibility of extension based on performance and funding. QUALIFICATIONS: Applicants should hold a PhD in Political Science, Sociology, Human Geography, Anthropology, or related
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novel statistical methods motivated by medical research needs Solid background in causal inference and survival analysis Experience with clinical trial research, machine learning, and high-dimensional