STAFF SCIENTIST 1-Computational Analysis of Human Regulatory Genomics NLM27-0015

National Institutes of Health/National Library of Medicine


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-the-art
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
· 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
· 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 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.

HOW TO APPLY: 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