Scientific Software Engineer, Computational Genomics Bioinformatics
We are seeking a highly motivated computational scientist with academic and/or industry experience to join our Computational Genomics team in the Translational Bioinformatics group. The mandate of Computational Genomics is to design, develop, integrate and manage a computational platform for Bioinformatics analysts that adheres to reproducible research best practices. This platform is used to address defined translational questions and to provide access to multi-omic data sets from preclinical data, clinical trials as well as public genomics data including incoming digital health data, and to facilitate access by the scientific community at BMS. Team work skills are essential to work effectively with bioinformaticians, statisticians and software developers as we continue to extend the scope of our reproducible research analytics platform.
- Contribute to the development, management and support of our core reproducible research analytics platform.
- Collaborate with IT experts to expand the Bioinformatics cloud computing infrastructure using our guidelines of reproducible research.
- Initiate and plan strategies to develop a framework to utilize digital health data within the context of genomics data.
- Collaborate with bioinformaticians, statisticians, biologists, and clinicians to identify critical questions that may be addressed via computational approaches.
- Ph.D. or Masters with 3+ years of relevant industry or academia experience is required. Education should be in the fields of Computer Science, Computational Biology, Bioinformatics, Molecular Biology, Biochemistry, or related disciplines.
- Knowledge of R is desirable.
- Ability to develop novel software to address scientific problems defined by research collaborators is required. Additionally, the ability to independently identify problems or new opportunities is required.
- Excellent communication and collaboration skills are essential in order to enable working across organizations.
- Sufficient knowledge of open source and commercial packages is required to recognize when existing software solutions are relevant.
- Ability to work in a Linux environment is required.
- Familiarity with statistical methods is desirable.
- Primary authorship of published open source code is highly desirable.
- Extensive experience in cloud computing including familiarity of Amazon's Cloud Web Services is desirable.
- Prior work in data integration, graph theory, semantic systems and/or published research on pharmaceutical disease areas is also desirable.