Clinical, imaging, and genetic data at scale are powerful tools for biological discovery and risk prediction. Carefully structured analyses and reproducible analytic pipelines accelerate ongoing efforts to gain clinically relevant insights.

Our research efforts are at the intersection of cardiovascular disease and human genetics--including both somatic and germline variation. Our clinical research efforts employ new techniques for deep phenotyping, such as deep learning. But these techniques rely on a solid foundation of classical bioinformatics. The Bioinformatics Programmer/Data Scientist will assist in managing, cleaning, and analyzing large scale medical data using a wide variety of analytic techniques, both in the cloud and with on-premises compute depending on data permissions. Experience with a cloud provider such as AWS or Google Cloud is a plus, and ability to learn how to manage cloud-based pipelines, and to perform cloud data management will be essential to learn. Maintaining bioinformatic databases by obtaining and restructuring data, including both UCSF proprietary data and public data, and writing tools to streamline discovery and replication analyses using these databases will be core responsibilities. An important task will be writing and maintaining analytic pipelines in languages such as R, python, Go, Rust, shell, SQL, WDL, and/or other appropriate languages, and using tools such as Docker. Experience with databases or the ability to learn will be requisite. Under the supervision of the PI, the Data Scientist will also be involved in data analysis, and will be comfortable with bioinformatic analyses including variant calling and annotation. There will be opportunities to employ cutting-edge methods and to develop new methods. The ability to learn and implement new techniques depending on the problem at hand will be an essential skill, thus requiring a strong foundation in computer programming. This position will also include administrative duties and will have the opportunity to participate in--and to lead--authorship teams.

The final salary and offer components are subject to additional approvals based on UC policy.

To see the salary range for this position (we recommend that you make a note of the job code and use that to look up): TCS Non-Academic Titles Search (https://tcs.ucop.edu/non-academic-titles)

Please note: An offer will take into consideration the experience of the final candidate AND the current salary level of individuals working at UCSF in a similar role.

For roles covered by a bargaining unit agreement, there will be specific rules about where a new hire would be placed on the range.

To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html