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Job no: 521090
Work type: Research Faculty
Senior management: College of Science
Location: Blacksburg, Virginia
Categories: Other, Research / Scientific, Data Analytics / Security
Research Scientist serving as a biostatistician supporting studies conducted by the Center for Biostatistics and Health Data Science at Virginia Tech. Engage in data wrangling, data management, and data analyses, largely within the area of computational cognitive neuroscience, including computational psychiatry. Write statistical methods sections and perform power analysis sections for grant proposals. Coordinate statistical activities with research project managers. Conduct appropriate statistical analyses using statistical languages (e.g., SAS, R) including interpreting and presenting results. Read and digest necessary biomedical and clinical research, applying appropriate classical and contemporary analytic techniques. Write and edit statistical methods sections for abstract and manuscript submissions. Provide complex statistical programming and analysis support for large datasets, including data from electronic health records and medical claims datasets. Much of the work will require experience in computational cognitive science and modern functional neuroimaging methodology.
PhD in Statistics, Biostatistics or relevant discipline; Significant experience in advanced statistical programming (e.g., SAS, R) with demonstrated experience writing advanced R scripts to summarize complex relationships; Demonstrated experience with deep learning and predictive analytics, simulation and data visualization; Familiarity with and experience using Github for reproducibility and version control; Significant experience in the application of traditional statistical modeling (logistic regression, Poisson regression, categorical data analysis, mixed effects GEE modeling, time-series analysis, structural equation modeling, etc); Bioinformatics experience, including metagenomics and epigenomics; Demonstrated experience working with large health related datasets (EHR, Claims, Biobank, etc).
Demonstrated expertise in time-series analysis, structural equation modeling, data reduction techniques; Demonstrated experience in computational cognitive science and modern functional neuroimaging methodology; Experience as a biostatistician in a collaborative, team-science research setting; Demonstrated collaborative publication record and experience as a co-investigator and/or biostatistician on NIH funded grants; Demonstrated experience mentoring graduate students or student interns in quantitative research studies.
Commensurate with experience
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.
Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.
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