The Bioinformatics Program in the Biostatistics and Epidemiology Division at RTI International has an opening for a Bioinformaticist, Early Career to contribute to development of bioinformatics tools, support and promote data interoperability, and analyze complex data sets. A fundamental understanding of biology, excellent verbal and written communication skills, and experience with scripting languages are essential.
Residing in the Bioinformatics Program of the Biostatistics and Epidemiology Division, the developer will have access to colleagues with expertise in genetics, genomics, high performance computing and software engineering who mentor junior staff to extend their skill set. Most work is accomplished by interdisciplinary teams, promoting innovation and collaboration.
The location of this position is Research Triangle Park, North Carolina.
- Contribute to the development of bioinformatics tools
- Work with colleagues to develop tools and methods to enhance data interoperability
- Learn new software and/or programming languages as needed
- Contribute to interdisciplinary teams; be a team player
- Learn and apply techniques for “omics” analyses
- Master’s degree in Bioinformatics, Computational Biology or related discipline or Bachelor’s degree with 2 years of relevant experience.
- Experience with the following is required:
- Experience managing, wrangling, or analyzing biological datasets
- Knowledge of “omics” data (e.g., sequence assembly and analysis)
- Experience with procedural or scripting languages (e.g. R, Python, Perl)
- Working knowledge of bioinformatics tools and resources
- Excellent verbal and written communication skills
- To qualify, applicants must be legally authorized to work in the United States and should not now or in the future, require sponsorship for employment visa status.
- Ontology development and representation (OWL)
- Experience with human subjects research data
- SQL or SPARQL
- High performance computing and/or cloud computing
- Development of data analysis and/or data visualization tools for biological data