Job ID: req1322
Employee Type: exempt full-time
Facility: Frederick: Ft Detrick
Location: PO Box B, Frederick, MD 21702 USA
The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and operated by Leidos Biomedical Research, Inc. The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.
Our core values of accountability, compassion, collaboration, dedication, integrity, and versatility serve as a guidepost for how we do our work every day in serving the public’s interest.
The Frederick National Laboratory is dedicated to improving human health through the discovery and innovation in the biomedical sciences, focusing on cancer, AIDS and emerging infectious diseases.
The Biomedical Informatics and Data Science (BIDS) Directorate works collaboratively and helps to fulfill the Frederick National Laboratory’s mission in the areas of biomedical informatics and data science by developing and applying world-leading data science and computing technologies to basic and applied biomedical research challenges, supporting critical operations, developing and delivering national data resources, and employing leading-edge software and data science to enable and advance clinical trials.
The Advanced Biomedical Computing Sciences (ABCS), part of BIDS, provides scientific computing, modeling, imaging, and bioinformatics support, engages in scientific consultation and collaboration, and offers training to NCI and NIH scientists and staff. The Data Solutions and Systems Biology (DSSB) group in ABCS strives to streamline and provide innovative solutions for the NCI/NIH community to access and use biological information collected across different sources and formats. Integrating diverse data sources to streamline project requests and analysis workflows, enable disease agnostic access and analysis, variant impact annotation, identifier conversions across species, and merging clinical and research data enabling translation from basic to the goal of precision medicine.
- Review existing text mining algorithms on rare disease informatics
- Identify and/or develop text mining algorithms to determine genotype/phenotype correlations in published literature
- Work with the manual curation team to review training and validation data sets on variants associated with rare diseases
- Work with the development team to build use cases and prioritize informatics tasks
- Document approaches and processes clearly and comprehensively
To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:
- Possession of a Bachelor’s degree in computer science, Math or Biomedical Science or a related field from an accredited college or university according to the Council for Higher Education Accreditation (Additional qualifying experience may be substituted for the required education)
- A minimum of two (2) years of experience in a related field
- Demonstrated ability to understand and develop literature mining algorithms
- Knowledge of literature mining complexities in determining genotype/phentotype correlations
- Knowledge of bioinformatics concepts and introductory programming skills
- Ability to self-direct with little or abstract day-to-day instruction
- Excellent written and verbal communication skills / ability to document and communicate complex scientific concepts for a variety of audiences
- Must be able to obtain and maintain a security clearance
Candidates with these desired skills will be given preferential consideration:
- Experience with developing context based literature mining algorithms
- Knowledge of Next Gen Sequencing and methods to determine rare variants
- Experience with web and database technologies.
Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)