Computational Research Scientist - Bioinformatics

BlueHalo has an opportunity available for a full-time research scientist to work with the Biological Research Team at Wright Patterson Air Force Base (WPAFB), OH. The successful candidate will have the opportunity to work across multiple collaborative projects in the areas of bioinformatics, data science, statistics, and multiple computational environments. The selected candidate will develop standardized data processing pipelines to assemble, annotate, and perform comparative analyses of microbial (fungal and bacterial) communities to aid in generation of testable hypotheses and identify targets for synthetic biology. The candidate will also lead the transition of reproducible workflows into cloud and high-performance computational ecosystems. This role requires effective teamwork and communication of results with colleagues from multiple technical backgrounds. Functions for this role will also include:

• Development and maintenance of scalable, reproducible bioinformatic data processing pipelines
• Management of large repositories of multi’omic datasets
• Assist in the analysis of enriched or natural complex microbial datasets generated from metagenomics and metatranscriptomics sequencing including tasks such as, but not limited to assembly, binning, annotation, enzyme mining, and phylogenetic analyses
• Documentation and presentation of research progress in the forms of reports, publications, and oral presentations
• Travel to scientific reviews and conferences

Requirements:

• M.S. (or Bachelor’s with 4+ years of relevant experience) in Bioinformatics, Microbiology, Microbial Ecology, Computer Science, Computational Biology, or similar degree programs
• Demonstrated success in applying or developing open-source software or workflows associated with bioinformatics
• Adept in the use of Python for bioinformatic tool development and deployment
• Knowledge of statistical computing in R
• Experience with distributed version control systems (e.g., Git) for code base development
• Proficient in Unix-based command line environments
• Experience in distributed computing environments such as HPC or cloud-based systems is highly desirable
• Experience with data processing pipeline development on Google Cloud Platform is highly desirable
• Previous experience in comparative genomics or an understanding of secondary metabolite biosynthesis is highly desirable
• Experience in applying machine learning algorithms or statistical methods to solving biological problems is highly desirable
• Demonstrated understanding of relevant public genomic databases
• Ability to work effectively in a multidisciplinary team, and communicate results clearly to non-computational scientists and other stakeholders
• Excellent organizational skills
• This position is working on-site at a government facility and requires U.S. citizenship