Postdoc Research Associate in Bioinformatics/Computational Biology | United States | UVA Health

Position:	Postdoc Research Associate in Bioinformatics/Computational Biology
Institution:	UVA Health
Location:	United States
Duties:	The research program in the lab focuses on developing computational methodologies and designing integrative data science approaches to study chromatin epigenomics and gene regulation. Current ongoing projects include: multi-omics integration-based algorithm development for transcriptional regulation prediction; model-based algorithm development for single-cell epigenomics and spatial multi-omics data analysis; statistical and computational modeling of phase-separated transcriptional condensation; global epigenetic and transcriptional regulation in T-cell immunity and various human cancer systems, etc
Requirements:	A Ph.D. or equivalent degree in any quantitative science, including but not limited to Bioinformatics, Computational Biology, Applied Mathematics, Statistics, Physics, Chemistry, Computer Science; Proficient in Python (or C/C++) & R programming; Strong quantitative background (e.g., statistical modeling, machine learning, computational or theoretical physics, etc.) or computational genomics experience (e.g., high-throughput sequencing data analysis, etc.)

Text:	Postdoc Research Associate in Bioinformatics/Computational Biology The research program in the lab focuses on developing computational methodologies and designing integrative data science approaches to study chromatin epigenomics and gene regulation. Current ongoing projects include: multi-omics integration-based algorithm development for transcriptional regulation prediction; model-based algorithm development for single-cell epigenomics and spatial multi-omics data analysis; statistical and computational modeling of phase-separated transcriptional condensation; global epigenetic and transcriptional regulation in T-cell immunity and various human cancer systems, etc A Ph.D. or equivalent degree in any quantitative science, including but not limited to Bioinformatics, Computational Biology, Applied Mathematics, Statistics, Physics, Chemistry, Computer Science; Proficient in Python (or C/C++) & R programming; Strong quantitative background (e.g., statistical modeling, machine learning, computational or theoretical physics, etc.) or computational genomics experience (e.g., high-throughput sequencing data analysis, etc.)