We’re looking for a post-doc and data scientist! See a description of the position below.
Zuckerberg San Francisco General Hospital and the Division of Cardiology is at the forefront of applying artificial intelligence and machine learning (AI/ML) to help improve outcomes in vulnerable and underserved populations. We are building out a ML predictive analytics team dedicated to the development and testing of ML algorithms that support the hospital’s performance improvement efforts, with an emphasis on health equity and algorithmic fairness. Our team charter is to improve patient care using data. We are dedicated to the translation of these algorithms into clinical practice and will be embedding all our algorithms into various clinical systems including the electronic health record (EHR) for rigorous testing and monitoring.
We are seeking a postdoctoral researcher and a data scientist to join our team. In addition to developing and testing ML algorithms, other responsibilities will include expanding the data warehouse, integrating new data sources (e.g. clinical notes), writing/editing research manuscripts, and more.
Our ML predictive analytics team is highly collaborative and includes team members with wide-ranging expertise:
- Jean Feng: Data analytics lead, assistant professor in the Department of Epidemiology and Biostatistics at UCSF
- Lucas Zier: Clinical lead, cardiologist at UCSF and ZSFG
- Jim Marks: Chief of the Medical Staff and Chief of Performance Excellence at ZSFG, anesthesiologist at UCSF and ZSFG
- Seth Goldman: Informatics Director for Technology Integration and Digital Health for the Office of Health Informatics for the San Francisco Department of Public Health, hospitalist at ZSFG
We are looking to hire a postdoctoral researcher and data scientist to join the team. The position (100% funded) will be for 2-years, with the possibility of extension. Salary and benefits are competitive.
The data scientist position requires at least a master’s degree or equivalent in computer science, data science, (bio)statistics, or another relevant field. We are looking for someone who:
- has experience training and testing machine learning algorithms for large datasets
- has experience with database design and creating ETL pipelines
The postdoctoral position requires a PhD degree or equivalent in computer science, data science, (bio)statistics, or another relevant field. We are looking for someone who:
- has experience in developing new ML algorithms
- has experience training and testing ML algorithms for large datasets
- can perform independent research
For both positions, the candidate should:
- be able to work collaboratively with a team
- has experience developing in a Linux environment, using git-based workflows, writing in Python, use high-performance computing
- have interest in analyzing Electronic Health Record (EHR) data and unstructured clinical notes
If you are interested in the post-doctoral position, please submit the following materials to :
- A cover letter
- A CV summarizing your education and work experience so far
- The names and email addresses of three references
- A code sample
- One representative publication (required for postdoc, optional for data scientist)
If you are interested in the data scientist position, please apply through this portal.
Screening of applicants will begin immediately and will continue as needed throughout the recruitment period.
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.