The Kleinstein Lab (Program in Computational Biology and Bioinformatics) is seeking two highly motivated researchers in computational immunology. These can be Associate Research Scientist (research rank faculty) or Postdoctoral Associate positions, depending on experience. The successful candidates will work in a highly collaborative environment on systems-level human immune profiling studies. Available projects include both computational methods development and applications in collaboration with experimental and clinical groups as part of grant-funded projects, such as the NIH Human Immunology Project Consortium (HIPC) and DARPA Assessing Immune Memory (AIM). Potential research areas include:
• Identification of signatures that relate to outcomes of human vaccination and infection.
• Development of multi-omics modules to support integrative signature analysis.
• Tensor decomposition methods for multi-omics immunology data analysis.
• Analysis of high-throughput single-cell B cell receptor (BCR) repertoire sequencing data.
Other areas of research focus that are consistent with the general themes of the lab are also possible.
The Kleinstein Lab pairs big data analyses with immunological 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. We currently make available the Immcantation framework, a start-to-finish analytical ecosystem for high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) datasets.
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.). We are seeking a candidate with interpersonal skills and that thrives in a collaborative environment, fostering teamwork and open communication.
Interested candidates should email a CV and short description of research interests.