The Cho and Hobbs labs at the Channing Division of Network Medicine at Brigham and Women's Hospital are looking for postdoctoral fellows to advance genomic research in the study of lung diseases. Our group has led some of the largest collaborative genetic and multi-omic studies in respiratory disease to identify novel genetic associations, disease genes, and pathways. The fellow will contribute to one or more R01-funded projects using whole genome sequencing, bulk and single cell RNA- and ATAC-Seq, and proteomics data, and participate in the Trans-Omics in Precision Medicine (TOPMed) Program. Analysis tasks include: genetic association analysis in multi-ethnic samples for COPD, pulmonary fibrosis, and other related phenotypes; expression analyses using bulk and single-cell RNA-Seq and proteomics data; molecular (RNA and protein) QTL analysis; functional fine mapping, and risk score and disease subtype identification using machine learning and network methods. The candidate will work with Dr. Michael Cho and Dr. Brian Hobbs, Associate and Assistant Professors of Medicine at Harvard Medical School and Brigham and Women's Hospital as part of an interdisciplinary and multi-institutional team, including genetic epidemiologists, biostatisticians, computer scientists, physicians, and molecular biologists.
Brigham and Women’s Hospital is a major teaching affiliate of Harvard Medical School and part of Mass General Brigham, the largest recipient of NIH funding among independent hospitals. The Division of Network Medicine is a research division within the Department of Medicine whose goal is to define the etiology and reclassify complex disease using network- and systems-based approaches. This group includes some of the largest population-based and pulmonary cohorts in the world, and an outstanding track record of mentoring.
Qualified candidates should have a Ph.D. in biostatistics, bioinformatics, or related quantitative field, with previous experience in analysis of large-scale omics data and strong programming skills in R / Bioconductor and/or Python. Specific experience with genetic association, single-cell analysis, and machine learning methods, are of added interest. M.D.'s with quantitative experience are also encouraged to apply. Candidates should also have excellent communication (oral and written) and documentation skills, adhere to reproducible research standards, and work well in teams and interact with all levels of staff.
Qualified candidates should submit their resume, the names of two references, and a cover letter to Dr. Michael Cho (firstname.lastname@example.org) and Dr. Brian Hobbs (email@example.com) Promising candidates will be invited for interviews and a presentation. Funding for this position is available immediately, but start time is flexible.