STAFF SCIENTIST 1, REFSEQ DATA WRANGLER
NATIONAL LIBRARY OF MEDICINE, BETHESDA, MARYLAND
Closing Date: November 21, 2020
The National Library of Medicine’s (NLM), National Center for Biotechnology Information (NCBI) is recruiting for a Staff Scientist 1 in the Information Engineering Branch (IEB) to contribute to NCBI’s human and mouse Reference Sequence (RefSeq) collection. NLM is a component of the National Institutes of Health (NIH), part of the Department of Health and Human Services (DHHS).
The IEB is looking for an outstanding candidate to help process and analyze data to improve NCBI’s human and mouse RefSeq annotation datasets. The candidate will be responsible for:
- collecting, processing, and analyzing new biological datasets available in repositories, such as Sequence Read Archive (SRA), Human Platelet Antigen (HPA), Genome-Wide Information on Protein Synthesis (GWIPS), and other public data sources;
- critically evaluating datasets and genome annotations to assess quality;
- evaluating software to aid in manual and automated gene annotation;
- developing and monitoring automated dataflows for loading data to production databases;
- providing critical expertise to NCBI in biological data curation of the human and other genomes using bioinformatics experience;
- user outreach to research scientists, data scientists, and clinicians; and
- interacting and collaborating with scientists within and outside the NIH.
The ideal candidate may or may not be a United States citizen and must have a doctoral degree and postdoctoral experience.
We are looking for an individual with:
- a strong publication record;
- a track record of outstanding research in genomics and expert knowledge in genomics, proteomics, mammalian biology, and regulation of gene expression in humans;
- general knowledge of sequencing techniques, genome assembly, and annotation methods and tools including BLAST, genome assemblers and aligners;
- expertise in bioinformatics of deoxyribonucleic (DNA) and ribonucleic (RNA) sequence analysis;
- expertise in the development of robust workflows for automated data processing, including alignment of RNA-Seq datasets and analysis compared to existing gene annotations, such as NCBI RefSeq;
- proficiency in Python;
- experience with SQL and shell scripting;
- experience in interpreting complex biological problems, critically analyzing the scientific literature, and demonstrating a thorough understanding of the strengths and weaknesses of high-throughput experimental datasets;
- excellent communication and organization skills; and
- a proven ability to successfully engage in multi-disciplinary collaborative research.
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 on a non-competitive appointment in the excepted service.
HOW TO APPLY:
Interested individuals should send a copy of their CV and Bibliography with 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 firstname.lastname@example.org. Please include the Job Announcement number, NLM27-0007, in the cover letter.
DHHS and NIH are Equal Opportunity Employers
Last Reviewed: October 20, 2020