July 26, 2021
Job Responsibilities Pre-Analysis (10%): Actively participate in the development of application portfolio by developing knowledge of internally developed systems, open-source programs, and commercial applications. Provide efficient data management support.
o Lead development of additional pipeline functionality and changes by providing knowledge of both collaboration-specific requirements and bioinformatics discipline advances Coding and code review (30%): Code and generally support code and applications on behalf of collaborative project and/or team. o Master best practices for project-based code development, QC, and execution consist with the expectations of specific collaborations o Perform and manage peer-to-peer code reviews by participating in informal and formal critical code reviews through GitHub Data Analysis and Application Development (30%): Analyze data of high complexity by applying sound statistical and commonly accepted bioinformatics methods to -omics data primarily under the direction of the collaborative project team o Develop multiple “specialty” analytical areas that serve one or more collaborative teams o Create flexible and scalable project-based R Shiny applications o Lead adoption of best practices in specialty analytical or biomedical areas by the bioinformatics group and peers Collaboration (20%): Lead bioinformatics portion of scientific collaborations as the primary bioinformatics resource o As bioinformatics point, assume management role for projects of low-to-moderate complexity, including all aspects of timelines, risk identification and mitigation strategies, and communication mechanisms o Directly manage all elements of project satisfaction and performance relative to scientific project aims o Promote continual objective, “hard” discussions about overall health of project and relationship o Develop new collaborations with moderate degree of supervision Academic Output (10%): Lead project-based presentations, grant sections, and manuscript sections with subsequent review by peers and mentors o Regularly contribute to manuscripts, conference posters, and/or platform presentations o Proactively contribute to bioinformatics and other sections of grant and award proposals
• MS/PhD in biological or computational discipline. • 5-10 years experience in applied bioinformatics, genomics, and computational work. This experience can be inclusive of a relevant PhD dissertation.
• Five (5) or more years of experience in applied bioinformatics, genomics, and computational work. This experience can be inclusive of a relevant PhD dissertation. • Demonstrable experience in project-level data harmonization and integration, including phenotype and genotype harmonization for multi-omics datasets, for cancer data resources is a plus. • Experience or knowledge of technologies commonly used in biological labs, such as next generation sequencing, PCR, cloning, electrophoresis gels, and cell culture.
Contact Krutika Satish Gaonkar (firstname.lastname@example.org) with questions.