Skip to Content

Computational Genomics

National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD and surrounding area

Position Description: 
The Laboratory of Cellular and Developmental Biology (LCDB) at NIDDK is a six-laboratory group with wide interests in applying computational techniques to answer questions related to differentiation and development by studying model organism and human genomics. We utilize a combination of wet bench and computational methods, in particular involving the analysis of hundreds of next-generation sequencing samples from RNA-seq, ChIP-seq, 4C-seq, and numerous other techniques. The computational team at LCDB actively develops and maintains open-source software and pipelines for high-throughput analysis of these experiments, with the aim of improving the quality and rigor of computational genomics.

We seek a computational biologist with a strong interest in collaborative interactions with biologists, and a desire to work with large data sets generated by a wide range of next generation sequencing techniques. The successful candidate will spend about half of their time working with biologists on a wide range of models and experiments, helping with experimental design, analyzing raw sequence data, assessing data quality, and assisting biologists with interpretation, manuscript preparation, and figure design. The other half of their time will be dedicated to independent software and methods development, that makes best use of the wide range of data prepared by LCDB. The exact nature of that independent work will be customized to the applicant's background and interest. They will also be involved in designing and teaching instructional content to biologists interested in learning statistics and computation; public presentations of their research both within LCDB and at conferences; and contribution to open-source software projects of their choosing.


  • masters or PhD in bioinformatics, biostatistics, biology, CS, mathematics, or related field
  • fluency in at least one of: C++, Python, R, Perl, or related language
  • experience with Linux: both general use of CLI, and software development
  • undergraduate-level familiarity with genetics/genomics


  • experience with statistical analysis in biology: generalized linear models, ANOVA, etc. (highly valued)
  • experience writing and documenting open-source software
  • familiarity with RNA-seq and ChIP-seq software packages: DESeq2, macs2, edgeR, etc.
  • familiarity with tools from modern genomics: bedtools, plink, GenABEL, mach/impute, etc.
  • development of statistical and computational models or algorithms in applied science
  • interest in science pedagogy and teaching of introductory statistics and CS to biologists
  • interest in applied machine learning methods
  • experience with scientific figure preparation, in R, Adobe Illustrator, Inkscape, or equivalent

To Apply: 
Interested individuals should send a cover letter including relevant experience, curriculum vitae with list of publications, and the names and contact information of three references via e-mail to Dr. Elissa Lei ( at the National Institutes of Health in Bethesda, MD. Applications will be reviewed upon receipt, and selected candidates will be contacted for a personal interview.

The NIH is dedicated to building a diverse community in its training and employment programs.