Bioinformatics Manager I (req2120)

Posted: 9/8/2021
Location: Frederick, MD
Employee Type: exempt full-time
Job ID: req2120

PROGRAM DESCRIPTIONThe Frederick National Laboratory is dedicated to improving human health through the discovery and innovation in the biomedical sciences, focusing on cancer,AIDSand emerging infectious diseases.The Biomedical Informatics and Data Science (BIDS) directorate works collaboratively and helps to fulfill the mission of Frederick National Laboratory 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 effectively enable and advancescience.The Advanced Biomedical and Computational Science (ABCS) group is a part of BIDS within Leidos Biomedical Research as a technological hub of translational scientists with expertise in structural biology, biology, chemistry, imaging, and informatics. ABCS develops state-of-the-art technologies in large-scale data modeling, analysis, and integration and supports the scientific research at the Frederick National Lab by helping translate scientific questions to technical solutions for cancer and biomedical research. 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.

KEY ROLES/RESPONSIBILITIES

  • Lead the rare disease informatics research project for ABCS
  • Providescientificand technicalleadershipfor bioinformatics and data science aspects of the project
  • Manage and supervise analysts supporting the project
  • Design and architect solutions for complex data integration aspectsofrare disease research
  • Write,reviseand submit scientific manuscripts on significant research findings
  • Interface with stakeholders, government sponsors and company management, and provide status reports, presentations, and application demonstrations

BASIC QUALIFICATIONS

To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:

  • Possession of Bachelor's degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in computer science, Bioinformatics, Biomedical Scienceor a related field or four (4) years relevant experience in lieu of degree. Foreign degrees must be evaluated for U.S. equivalency
  • In addition to educational requirements, a minimum of four (4) years progressively responsible bioinformatics experience, including two (2) years of experience in a supervisory/leadership capacity
  • Experience managing bioinformatics and/or data science analysts
  • Demonstrated ability tounderstand and developmachine learningalgorithmsin the bioinformatics field
  • Experience analyzinggenomicsand/orchemoinformaticsdata sets
  • Demonstrated experience implementing solutions for complex structured andunstructuredscientific data integration
  • Expertise in R and Python
  • Experience with Unix/Linux OS scripting
  • Experience with high performance computing
  • Excellent knowledge of scientific data sets in the public domain
  • Excellent written and verbal communication skills/ability to document and communicate complexscientificconcepts for a variety of audiences
  • Ability to obtain and maintain asecurityclearance

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

  • Masters or PhD in bioinformatics or a related field
  • Experience with web and database technologies
  • Experience with NGS analysis
  • Experience with natural language processing and literature mining
  • Knowledge of rare disease research and associated complexities