Summary Baylor College of Medicine is seeking a highly motivated Postdoctoral Research Associate for an integrative analysis of transcriptomic, epigenomic, and proteomic large-scale datasets, under the joint supervision of Dr. Cristian Coarfa and Dr. Andrew DiNardo. This is an opportunity for an ambitious scientist committed to advancing their academic career, who demonstrates strong work ethic, exceptional initiative, and an innovative, analytical approach to solving complex scientific problems. The position will involve analysis of DNA methylation, single cell RNA and ATAC sequencing, Fiber-sequencing, and data science approaches to support research aimed at understanding long-term molecular changes induced by infections, in particular tuberculosis and other respiratory infections. Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates. Job Duties Analyzes single cell RNA-Sequencing, single cell ATAC-Seq, CITE-Seq, as well as bulk RNA-Seq, Proteomics, Metabolomics, and other datasets, generated from tuberculosis patient cohorts with rich clinical data. Performs advanced modeling of post-tuberculosis lung disease risk using approaches including generalized linear models and deep learning. Performs other job-related duties as assigned. Minimum Qualifications MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications Ph.D. in Computer Science, Bioinformatics, or Biology, with a strong background in statistics and familiarity with large datasets such as proteomics or sequencing. Experience in epigenetics or gene regulation is a plus. Experience with statistical analysis tools such as R or Python is required (Candidates will be expected to pass a basic programming test in Python). Excellent written and verbal English skills, strong communication and interpersonal skills, and the ability to work within large collaborative teams.