The Kleinstein Lab (Program in Computational Biology and Biomedical Informatics) is seeking a highly motivated researcher in computational immunology to work in close collaboration with the Yildirim Lab to identify molecular signatures defining sickle cell disease (SCD) and reduced vaccine response by analysis of systems-level data profiling innate immunity and long-term adaptive immunity among children and adults with SCD. The position can be Associate Research Scientist (research rank faculty) or Postdoctoral Associate, depending on experience.
The successful candidate will be part of an interdisciplinary team with expertise in human immunology, vaccine response, sickle cell disease, antibody response, proteomics, and computational biology to carry out the proposed studies. The project is funded by multiple NIH grants, including the NIH Human Immunology Project Consortium (HIPC), a highly collaborative national network that the successful candidate will join. Available areas of research include both computational methods development (e.g., multi-omics, adaptive immune receptor repertoire sequencing (AIRR-seq), scRNA-seq+BCR/TCR) and applications to understanding disease and vaccination responses in SCD patients. Other areas of research focus that are consistent with the general themes of the labs are also possible.
The Kleinstein Lab pairs big data analyses with immunology domain expertise to better understand how the dynamic processes of the immune system drive 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. They currently make available the widely-used Immcantation framework, a start-to-finish analytical ecosystem for high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) datasets.
The Yildirim Lab studies innate and adaptive immune signatures of vaccine response in vulnerable populations, such as transplant recipients and individuals with sickle cell disease, using different tools including multicolor flow cytometry, single cell mRNA transcriptomics (scRNA-seq), and quantitative/functional antibody assays. They conduct laboratory and field- based studies in low- and high-income settings globally and have experience in phase 1 to phase 3 clinical trials for vaccines against different pathogens such as pneumococci, pandemic and seasonal influenza, respiratory syncytial virus (RSV), EBOLA, SARS-CoV2, and Chikungunya virus.
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/biology. A Ph.D. in a quantitative discipline is desired (Bioinformatics, Computer Science, Statistics, Physics, Applied Mathematics, etc.). We are seeking a candidate with interpersonal skills and that thrives in a collaborative environment, fostering teamwork and open communication.
Interested candidates should send a CV and short description of research interests to: steven.kleinstein@yale.edu
