Functions/Duties of Position
We are seeking a skilled scientific programmer to develop genomic, imaging, and clinical analysis applications on a distributed data / workflow management and analytics platform currently under development. This position will work in a team oriented software development environment, following best practices such as code sharing through GitHub and development of structured software APIs. A successful candidate will contribute to the international development of standardized APIs and data schemas, and develop implementations compatible with such APIs, ensuring that the system is interoperable within the emerging community ecosystem of software tools.
- Develop custom analytics and data management applications to facilitate one or more of the following: large-scale genomic data analysis; machine learning methods to infer genotype-to-phenotype predictive models; analysis of quantitative imaging data.
- Work with the platform development team to implement scalable cloud-enabled workflows to disseminate analytical advances to the research community.
- Establish and maintain standards for structured software & systems engineering, including requirements, design, code, test, quality, configuration & release management and project management.
- Provide documentation and user support allowing computational researchers across campus to access and re-use analysis tools.
- Maintain well-curated, highly structured, transparent omics, imaging, or clinical data resources.
- Develop tools to integrate commonly used open source bioinformatics software applications.
- Participate in leading international efforts aimed at establishing best practices and standards for genomic data representation and analysis.
We welcome candidates with* doctorate or master’s degrees in computational biology, computer science, or related technical disciplines. Candidates with bachelor’s degrees and significant accomplishments in real-world work experience will also be considered.* Candidates will be hired at the appropriate position rank (e.g. research associate or senior research associate) and pay-scale based on education level and work experience. Academic appointments at the research assistant professor level may also be available for qualified candidates.
- Advanced skills in a high level programming language, preferably Python, R, or Java.
- Experience in one of the following:
Analyzing next-generation DNA or RNA sequencing data.
- Advanced machine learning or statistical techniques, such as probabilistic graphical models, Bayesian inference, and optimization methods.
- Image processing algorithms and biomedical image analysis workflows.
- Experience using structured engineering methods for specifying, designing, and implementing systems.
- Experience with architecture and tools for managing “omics” or imaging data.
- Ability to prioritize multiple tasks at one time.
- Excellent communication, analytical and organizational skills, both written and verbal.
- Ability to work independently and as part of a team while being collaborative in resolving problems.
- A desire to change the world and contribute to the elimination of human disease.
- At least three years of experience with distributed file systems, such as Lustre, and working with “big data”.
- Masters or doctorate degree preferred.
- High performance computing experience in a Unix/Linux environment.
- For image analysis, familiarity with commonly used tools such as Slicer or CellProfiler.
- Experience in a professional, team-oriented software development environment.
- A passion for open-access innovation.