National Institutes of Health (NIH)

Staff Scientist Position

Department of Health and Human Services National Institutes of Health

Bethesda, MD, United States

Staff Scientist Position

Position Description:
The Laboratory of Receptor Biology and Gene Expression (LRBGE), Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH) and the Department of Health and Human Services (DHHS) is recruiting a Staff Scientist in Computational Biology to join the laboratory of Dr. Shalini Oberdoerffer, in Bethesda, MD. The position supports ongoing scientific efforts in the epigenomic and epitranscriptomic regulation of mRNA processing and function. Additional information regarding the Oberdoerffer group is available at

About NCI’s Center for Cancer Research
The Center for Cancer Research (CCR) is an intramural research component of the National Cancer Institute (NCI). CCR’s enabling infrastructure facilitates clinical studies at the NIH Clinical Center, the world’s largest dedicated clinical research complex; provides extensive opportunities for collaboration; and, allows scientists and clinicians to undertake high-impact laboratory- and clinic-based investigations. Investigators are supported by a wide array of intellectual, technological, and research resources. For an overview of CCR, please visit

Eligible candidates must have a Ph.D. or equivalent degree in bioinformatics, computational biology, biostatistics or related field and relevant postdoctoral experience. The Oberdoerffer laboratory examines the role of DNA methylation in co-transcriptional pre-mRNA splicing, and the influence of mRNA modifications in post-transcriptional mRNA regulation. Building on their recent publication (Arango et al., Cell, 2018), the position to be filled will specifically examine the role of mRNA acetylation in promoting mRNA stability and efficient translation in immune and cancer relevant cellular model systems. While candidates with a wide range of expertise will be considered, a strong theoretical background in gene regulation and RNA biology is essential. This position will involve the development and implementation of computational tools for precision mapping of modified nucleotides related to the net impact on mRNA expression. Experience in the analysis of next generation sequencing data and excellent programming skills (python, R, C/C++, Java) will be required. Currently utilized platforms include genome and transcriptome-wide analysis of DNA methylation, mRNA expression, pre-mRNA splicing, mRNA stability, and translation (ex. Bisulfite-seq, RNA-seq, BRIC-seq and Ribo-seq). The laboratory is further developing Oxford Nanopore technology for single-molecule determination of complex mRNA splicing patterns and site-specific mapping of modified nucleotides. Experience in machine learning algorithms will be considered a bonus. The successful candidate will be an accomplished and independent computational biologist with a track-record of training student interns and junior fellows. Candidates seeking a postdoctoral position will also be considered.

Staff Scientist salary is commensurate with education and experience. A full benefits package is available, including retirement, health insurance, life insurance, long-term care insurance, annual and sick leave, and Thrift Savings Plan (401k equivalent). This position is not restricted to U.S. citizens.

To Apply:
Please send cover letter, curriculum vitae, bibliography, and statement of research interest to:
Dr. Shalini Oberdoerffer by email or regular mail.
E-mail address:
Postal address:
41 Medlars Drive
Rm. B626
Bethesda, MD 20892
Review of applications will begin on May 10th, 2019.

This position is subject to a background investigation. The NIH is dedicated to building a diverse community in its training and employment programs.

DHHS, NIH, and NCI are Equal Opportunity Employers


Apply with CV and Cover Letter

Must be a .doc, .docx, or .pdf file and no larger than 1MBMust be a .doc, .docx, or .pdf file and no larger than 1MB

Staff Scientist Position