The Bakar Computational Health Sciences Institute (BCHSI) is looking to recruit a Postdoctoral Research Scholar with expertise in biomedical informatics and the analysis of Electronic Health Records (EHR) data. This postdoctoral research scholar will oversee the application of modern methodologies to retrospective and prospective datasets to uncover ‘real-world evidence’ on a range of diseases and treatments. The scholar will utilize several informatics tools, as well as statistical and machine learning methods to address research questions in the context of ongoing collaborations with industry sponsors and the FDA itself. Candidates will be expected to perform innovative research using both structured and unstructured EHR data, and may also utilize publicly available data and resources such as biomedical ontologies.

Successful candidates will be working on real-world data/evidence projects funded by the US Food and Drug Administration (FDA), NIH, and by pharmaceutical and biotech companies.

A primary appointment in BCHSI will be provided, along with an affiliation in the Department of Pediatrics.

BCHSI and UCSF took a leadership role in 2015 in helping organize a central health data warehouse across the entire University of California.  The University of California Health System, with 20 health professional schools (6 medical schools), 6 academic health centers, and 12 hospitals, is the tenth largest health system in the United States by revenue, and has now built a secure central data warehouse (UC Health Data Warehouse, or UCHDW) for operational improvement, promotion of quality patient care, and to enable the next generation of clinical research.  The repository currently securely holds data on over 7 million patients seen since 2012, treated by nearly 100,000 health care providers in over 200 million encounters, with over 560 million procedures, more than 760 million medication orders and prescriptions, and with over 2 billion vital signs measurements and test results. Over 600,000 of these patients are primary care patients.  The majority of these patients live in California, the most diverse state in the United States.  De-identification of the data has already been completed to enable clinical research projects, under guidance from UC campus institutional reviews boards, privacy and compliance officers, and information security officers. This data is stored in the Observational Medical Outcomes Partnership (OMOP) vendor-neutral open data model, enabling a wide range of software tools and computational methods to be used consistently with other state and national efforts.  This data is currently centralized and available in a Microsoft Azure Databricks secure cloud environment enabling research and development in artificial intelligence and machine learning.  This data helps enable a community of more than 400 researchers in machine learning and artificial intelligence at all levels across the 10 campuses and 3 national labs of the University of California.  Successfully recruited candidate would be working with this extremely unique database.