Healthcare Data Science: Discovering and Distributing the Latent Knowledge Embedded in Clinical Data
In Stanford's Center for Biomedical Informatics Research, you will have the opportunity to work in close collaboration with clinicians, scientists, and healthcare systems with access to deep clinical data warehouses (e.g., electronic medical records), broad population health data sources (e.g., national claims), and professional development resources like (grant) writing workshops and clinical shadowing experiences. Research topics range from machine learning, designing, and evaluating clinical decision support content to disintermediate scarce medical consultation resources, evaluating large-language model applications in healthcare systems, systematically identifying ineffective clinical processes, data-mining audit logs of electronic clinical activity, as well as more conventional outcomes research on the implications of physician practice against challenging issues in healthcare.
Specific near-term (funded) projects include:
(1) Measuring, predicting, and implementing appropriate antibiotic use for common infections using electronic phenotyping, supervised machine learning, live Epic/FHIR implementations for silent deployment, and multi-site data coordination.
(2) Developing collaborative filtering recommender algorithms to predict specialty care and large-language model based user interfaces to power automated electronic consultation services to expand access to healthcare services.
(3) Identifying patients in multi-site electronic medical records who received treatment for substance use who either did or did not continue with longer-term treatment. Developing models to predict and identify candidate risk factors for such treatment retention using both structured clinical data and keyword concepts extracted through a natural language processing methods.
(4) Analyze hospital direct costs per encounter to identify areas of undesirable variability with the potential to improve through standardization.
(5) Improving diversity in clinical trial recruitment by targeting outreach through electronic medical records.
The position will allow for the exploration of additional research threads further tailored to the applicant's interests and career goals.
The strongest applicants will have experience in one or more key interdisciplinary areas (not all are expected, that's the point of learning together):
Computer Science or Informatics:
Proficiency in programming and software development with a habit for robust unit testing. Our group mainly develops software in a Python + SQL environment with R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design and the human-computer interaction testing experience will be valuable.
Statistics and Mathematics:
Machine learning (supervised and unsupervised) methodology and evaluation including discrimination vs. calibration measures and (hyper)parameter optimization through cross-validation. Observational research methods including interpreting multivariate regression, missing data imputation, propensity score matching, and bootstrap simulations.
Biomedical / Healthcare Science:
Understanding of clinical decision-making processes, healthcare quality metrics, financial incentives, and decision support interfaces and pitfalls.
A Ph.D. in a quantitative field with a strong programming and statistics background
Track record of completed research projects
Well-written, peer-reviewed papers are expected.
Specific responsibilities and research projects will be tuned to the career goals, technical strengths, and interests of the applicant.
Required Application Materials:
Example research paper
A brief career goal statement (that reflects alignment with the projects we would likely pursue together)
Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.
Faculty Sponsor (Last, First Name):
Stanford Departments and Centers:
Med: General Internal Medicine
Neurology & Neurological Science
Postdoc Appointment Term:
1 year minimum with the option to extend. $75,000+ per year + post-doc benefits
Appointment Start Date:
How to Submit Application Materials:
Email application materials to email@example.com