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of national research infrastructures. The ideal candidates will have a PhD in a discipline closely related to computational social science by date of appointment (e.g. network science, computer science, data
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through the implementation of the Coping Power Rural Program , Double Check Online program, Integrative Data Analysis Projects, the mental health screening of students, and related evidence-based programs
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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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recruitment and buy-in, CARE program implementation and fidelity of implementation monitoring, and data analysis and manuscript generation. This position will complete duties as follows: Recruiting: Reaching
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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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the development of novel therapies for coronary microvascular disease. The research program focuses on clinical translation and the development and validation of existing and novel cardiac imaging-based
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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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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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: 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