Microbial genomes harbor tremendous diversity at the gene level even within closely related taxonomic groups. Microbes exchange DNA, with each other and with viruses, and can also take up DNA from other sources in the environment. Microbial ecosystems, therefore, are an evolving social network of interacting and mobile genes with the capacity for tremendous functional plasticity.
We seek to understand why the same clinical intervention or condition -- for example administration of a drug or infection with a pathogen -- can lead to different outcomes in individual patients. We focus on the role of the microbiome in clinical outcomes, in particular we try to predict how an individual's gut will metabolize a drug.
We study the temporal dynamics of microbial communities and interactions between co- occurring populations of microbes and viruses to identify drivers of transitions between microbial community states.
We have positions available for:
We are looking for a postdoctoral fellow with significant experience in computational biology to study functional diversity in natural communities of microbes. Application instructions here >>
Graduate students -
We are looking for PhD or MD/PhD graduate students who are interested in 1) studying the contributions of the commensal microbiome to energy acquisition and drug metabolism in the human body and 2) developing new computational techniques to study genetic exchange and community stability and structure using large-scale genomics datasets. Apply via Graduate Programs in Biomedical Sciences at Einstein.