We are always on a lookout for talented individuals who share our passion of functional genomics and would like to work in a highly collaborative and dynamic environment. Currently, we are seeking highly qualified postdoctoral candidates in two key areas detailed below. To apply, please send your cover letter, CV, and contact information for at least two references to peter.kharchenko@post.harvard.edu.

Statistical analysis of sequencing data

Rapid progress of short-read DNA sequencing technologies provided means to capture many aspects of the cellular state, such as transcript abundance (RNA-seq) or regulatory/epigenetic state (ChIP-seq). These functional assays rely on sequence sampling, and require intensive computational analysis to separate biologically significant signals from background noise and systematic bias. This is a dynamic field, as new assays being developed by our collaborators as well as other groups, and increasing availability of large-scale datasets, require new statistical methods and algorithms for analysis.

Much of the work will be conducted in close cooperation with our experimental collaborators, on projects requiring integrative analysis of epigenetic, transcriptional and other data in the context of specific biological processes (e.g. cell differentiation, dosage compensation, etc). The candidate will also work on development and deployment of novel computational tools, aimed for instance, at comparative analysis of large-scale epigenetic datasets.

Requirements:

  • A strong interest in conducting collaborative research on the topics outlined above is paramount.
  • PhD degree in Computational Biology, Bioinformatics Biophysics, or a related discipline.
  • Track record of publications in peer-reviewed journals.
  • Expertise in statistical methods (e.g. Bayesian statistics, expectation-maximization) and algorithm development in the context of biological systems.
  • Experience in analysis of functional sequencing data, such as RNA-seq or ChIP-seq is advantageous.
  • Proficiency in R and Bioconductor. Knowledge of C/C++ and Java, as well as general proficiency with UNIX operating systems is strongly desired.
  • Excellent communication skills.

Microfluidic devices for cellular assays

While modern sequencing-based assays can be remarkably informative, their application to investigations of specific cellular structures or rare cell types is typically limited by the variability of sample processing and the amount of labor required to examine sufficient number of samples. We are aiming to bridge this gap by performing key aspects of the protocol in computer-controlled microfluidic devices.

The researcher will be tasked with developing and applying custom microfluidic designs for genome-wide analysis of gene expression, epigenetic marks and other genomic properties of small samples or single cells. The projects will aim to elucidate epigenetic and regulatory alterations associated with pathological conditions in complex mammalian tissues. The researcher will have an opportunity to work in close cooperation with the collaborators expert in the models, assays, and pathologies being investigated. Similarly, the researcher will be able to draw on the computational expertise of the lab for integrative analysis of genomic data.

Requirements:

  • Excellent expertise in developing microfluidic devices for cellular assays.
  • Strong interest in conducting collaborative research on regulation of mammalian tissues at a molecular level.
  • Interest in next-generation sequencing assays.
  • PhD degree in Engineering, Biophysics, or a related discipline.
  • Track record of publications in peer-reviewed journals.