20 post-doc-computer-graphics Postdoctoral positions at University of Virginia in United States
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research program sponsored by federal agencies such as the U.S. Department of Defense and the National Science Foundation (NSF). The focus of the research is on developing innovative physics-informed deep
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Collaborate with leading researchers within and outside UVA Qualifications: U.S. citizenship required Ph.D. in Data Science, Statistics, Computer Science, Network Science, Physics, Engineering, Sociology
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applicants interested in developing a research program in the field of cancer biology are welcomed to apply. Expertise in the fields of molecular biology, cell biology, and genetics are expected. Experienced
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Communicate results through peer-reviewed publications, internal and external presentations, conferences, and websites. Minimum Requirements: Doctoral degree in a quantitative discipline such as computer
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: Implement computational approaches to analyze and integrate genomic data, inclduing whole genome sequencing, single-cell RNA-seq, and single-cell cell surface protein-seq (CITE-seq). Utilize an array
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experimental and computational angles. The candidate will have opportunities to drive his/her own research project(s), develop fellowship applications, write manuscripts, mentor junior trainees, and learn skills
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Dr. Patrick Finan’s multidisciplinary pain research team is inviting applications for a Postdoctoral Research Associate position, starting in January 2025. This opportunity is within the Department of Anesthesiology at the University of Virginia School of Medicine .. The Finan Lab ’s goals...
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sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs. The University of Virginia is an equal opportunity
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primarily a sedentary job involving extensive use of desktop computers. The job occasionally requires local and regional travel to schools for recruitment and coaching, and walking some distance to attend
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world