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Staff Scientist 1 - Computational Analysis of Human Regulatory Genomics

The National Library of Medicine’s (NLM), National Center for Biotechnology Information (NCBI) is recruiting for a Staff Scientist 1. The position supports interdisciplinary research in the Computational Biology Branch (CBB). NLM is one of the 27 Institutes at the National Institutes of Health (NIH), part of the Department of Health and Human Services (DHHS).

NLM is looking for an outstanding candidate to conduct research in computational analysis of human regulatory genomics. The candidate will develop state‐of‐theart deep learning methods for the accurate prediction of enhancers and silencers, identification of disease‐causative mutations, and reconstruction of cell‐type specific regulatory architecture of the human genome. This position is responsible for:

  • developing machine learning methods. including deep learning methods;
  • performing statistical analyses, devising new computational methods, and creating analytic models;
  • analyzing large genomic and epigenetics datasets;
  • working in collaboration with other experimental and computational laboratories at the NIH;
  • publishing scientific manuscripts and presenting at conferences and meetings;
  • mentoring students and postdoctoral fellows; and,
  • staying abreast of bioinformatics and deep learning methods as well as genomic resources.


The ideal candidate may or may not be a United States citizen and must have a doctoral degree.

We are looking for an individual with several of these qualifications or talents:

  • a Ph.D. in a quantitative field, such as Computer Science, Mathematics, Computational Biology, or Bioinformatics;
  • at least two years of relevant postdoctoral experience;
  • a strong track record in research as evidenced by peer‐reviewed publications;
  • research experience in regulatory genomics, statistics, evolutionary biology, gene regulation, epigenomics, computational disease genetics, and genomic and epigenomic architectures of cellular identity;
  • research experience and/or up‐to‐date understanding of the principles of eukaryotic gene regulation;
  • hands‐on experience on working with the Encyclopedia of DNA Elements (ENCODE), NIH Roadmap Epigenomics, Ensembl, and similar databases;
  • experience developing deep learning algorithms, methods, and tools;
  • fluency in Python, R, and MATLAB, including TensorFlow, PyTorch and/or Theano libraries;
  • experience working with GPU‐based architectures;
  • proven ability to work on interdisciplinary projects;
  • mentoring experience;
  • ability to communicate effectively, both verbally and in writing; and
  • ability to work both independently and as a team member.

Salary is commensurate with research experience and accomplishments. A full package of benefits, including retirement, health, life, and long‐term care insurance, Thrift Savings Plan participation, etc., is available. The successful candidate will serve in a non‐competitive appointment in the excepted service.


Interested individuals should send a copy of their CV and Bibliography with the names of three references along with a cover letter detailing research interests, a brief summary of communication and organizational skills, and evidence of engagement in multi‐disciplinary collaborative research to Please include the announcement number, NLM27‐0015, in the cover letter. Applications will be accepted until the position is filled.

DHHS, NIH, and NLM are Equal Opportunity Employers

Last Reviewed: April 18, 2023