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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
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interplay to regulate tumorigenesis. Our research focuses on identification of the cell of origin and elucidating the role of tumor microenvironment in cancer development. We dissect the cellular and
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, spanning computational data analysis, community-based participatory research, community needs assessments, partnership-building, and related grant development opportunities. The successful candidate will be
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Center. The broad areas of interest in Dr. Trinh's lab include: gene regulation by RNAs and proteins, modulation of gene-specific chromatin architecture, blood development, cancer and genetic diseases
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are responsible for developing two courses in one (or two) of the Engagement pillars. For more information about the Engagements, visit: http://gened.as.virginia.edu . Postdoctoral Research Associates teach six
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targeted to better clinical outcomes. The laboratory also has the goal of therapeutic development to these targets. The ideal candidate should possess substantial knowledge and skills to foster innovative
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. This position will focus on developing and applying novel statistical methods, machine learning approaches, and AI-driven computational tools, with a strong focus on statistical genetics and genomics
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congenital human disorders, potentially leading to the development of novel therapeutics for related human diseases. For more information about the Tang Lab can be found through: https://med.virginia.edu/bmg
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of the brain and development of novel therapeutics. The Mailman lab focuses on mechanisms of drug receptor interaction, and the discovery and development of CNS drugs. Our laboratory discovered the first
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network modeling to address real-world policy challenges through algorithm development and technical analysis. Key Responsibilities Conduct original research in generative AI Train and supervise graduate