Staff Scientist 1
NATIONAL LIBRARY OF MEDICINE, BETHESDA, MARYLAND
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 27 Institutes at the National Institutes of Health (NIH) of the Department of Health and Human Services (DHHS).
NLM is looking for an outstanding candidate to conduct research, devise new methods, and develop programs to answer important questions in several areas of computational biology. This position is responsible for:
- performing interdisciplinary research;
- designing algorithms, devising new computational methods, and developing stand-alone and web-based applications;
- maintaining and improving previously developed in-house programs;
- providing support to users of the developed software;
- mentoring postdoctoral fellows, students, and postbaccalaureate fellows; and,
- staying abreast of bioinformatics and emerging computational biology methods.
The main requirement of this position is to develop new computational algorithms, such as deep learning models, for exploring the mechanisms of gene regulation. Duties include:
- identifying the target genes of non-coding regulatory elements, such as enhancers;
- classifying regulatory elements;
- developing machine learning models to identify de novo regulatory elements and cooperation among them;
- identifying disease causative variants;
- setting strategic development priorities for research projects; and,
- ensuring that development targets are met on time and within budget.
The person in this position will:
- work with a team of multiple scientists and trainees including postdoctoral fellows, and student and postbaccalaureate fellows;
- be responsible for managing timelines and priorities;
- develop novel deep learning models and genomic analysis tools to explore gene regulation and key non-coding variants associated with diseases;
- assist in generating innovative computational methods and improving downstream analyses with scientists in the NCBI, NIH, and outside the NIH; and,
- have expertise in machine learning and genomic studies.
The position aligns with department objectives to make the interpretation of biomedical data accessible and useful to scientific research, public health, and the general public through efficient and effective modern IT practices and innovative design strategies and publications. It allows us to fulfill a key goal in NLM’s Strategic Plan: supporting "research in biomedical and health information access methods and information dissemination strategies."
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:
- a Ph.D. in a quantitative field, such as Physics, Mathematics, Computational Biology, etc.;
- at least seven years of relevant postdoctoral experience;
- a strong track record in research as evidenced by peer-reviewed publications;
- research experience in machine learning algorithms, construction of gene regulatory networks, enhancer-gene regulatory mechanisms, mathematical modeling of regulatory program, and the discovery of disease causal variants in non-coding regions;
- familiarity with Next Generation Sequencing (NGS) data and relevant tools, such as genome assemblers, aligners, and variant callers;
- proven ability to apply mathematical modeling to a broad range of problems;
- fluency in Perl, Python, and R;
- demonstrated experience in scientific programing and development of web applications;
- proven ability to work on interdisciplinary projects not directly related to his/her training;
- mentoring experience;
- demonstrated ability to communicate effectively, both verbally and in writing; and,
- proven 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 email@example.com. Please include the announcement number, NLM 27-0010, in the cover letter. Applications will be accepted until the position is filled.
DHHS, NIH, and NLM are Equal Opportunity Employers
Last Reviewed: February 3, 2021