The Kleinstein Lab (Yale School of Medicine, Department of Pathology) is seeking a highly motivated postdoctoral associate in computational immunology. The successful candidates will work in a highly collaborative environment on systems-level human immune profiling studies, with a specific focus on high-throughput B cell receptor (BCR) and T cell receptor (TCR) repertoire analysis (including bulk and single cell RNA-seq + BCR). For interested candidates, there are opportunities for computational methods development.
The Kleinstein lab pairs big data analyses with immunological expertise to better understand how the dynamic processes of the immune system affect the course of infection, vaccination and autoimmunity. The lab has developed many widely used analysis methods for high-throughput immune profiling data, particularly transcriptomic and B cell receptor repertoire sequencing data. We currently make available the Immcantation tool suite, a start-to-finish analytical ecosystem for high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) datasets.
The biological applications for this position will be related to ongoing NIH-funded collaborations with several experimental/clinical labs, including:
The Shelli Farhadian Lab: The scientific focus of the Farhadian laboratory is to study the neurological effects of systemic infections. The research group focuses on immune and gene expression correlates and biomarkers of neurological dysfunction during and following acute infection. Studies are primarily translational, involving research participants recruited locally. The postdoc will collaborate on studies generating transcriptomic, including AIRR-seq, datasets to characterize patient cohort biospecimens, including from those with acute and post-acute COVID-19, HIV and other infections, with a goal of understanding central nervous system viral immunity through detailed analysis of cerebrospinal fluid immune cells.
The Kevin O’Connor Lab: The scientific focus of the O’Connor lab is to define the mechanisms by which B cells, and the antibodies they produce, affect tissue damage in autoimmunity. A major goal is to define the mechanisms of autoantibody production in human neurologic autoimmune diseases with the aim of improving therapeutic approaches. Examples of specific projects include characterizing the B cell repertoire (using bulk and single cell RNA-seq + BCR) to understand (i) B cell trafficking between disease specific tissues and blood, (ii) B cell clonal persistence through disease course and treatment, (iii) identify correlates of clinical status, and (iv) defining candidate biomarkers correlating with treatment response.
Other biological areas of focus may include Influenza vaccination, Lyme disease and West Nile Virus infection as part of the NIH HIPC.
The ideal candidate will have strong quantitative and programming abilities (ideally R and Python), along with an interest in applying these skills to problems in immunology. A Ph.D. in a quantitative discipline is desired (Bioinformatics, Computer Science, Statistics, Physics, Applied Mathematics, etc.).
Interested candidates should forward a CV and short description of research interests together with the names and addresses of three references to: steven.kleinstein@yale.edu
Yale University is an affirmative Acton/Equal Opportunity Employer and welcomes applications from women, persons with disabilities, protected veterans and member of minority groups.
Review of applications will begin immediately and will continue until the position is filled.