Research Scholar in Computational Health Policy (1 Year Fixed Term)

Stanford, California, United States

Research

Post Date May 08, 2024

Requisition # 103176

Stanford’s Department of Health Policy (DHP) invites applicants for a full-time Research Scholar (1 year fixed-term) position to work in simulation modeling and algorithmic fairness for informing policy.

DHP produces interdisciplinary, world-class research on domestic and international health that advances our understanding of how health care can be delivered, and shapes the formulation of health care policy around the world. DHP seeks a Research Scholar in Computational Health Policy to join the Stanford Health Policy Data Science Lab led by Professor Sherri Rose. The Health Policy Data Science Lab develops and applies quantitative methods to solve high impact problems in health policy.

The Research Scholar will be responsible for leading innovative, collaborative scientific research to develop and apply simulation models of diseases processes, the health care system, and the impact of algorithms while factoring in algorithmic fairness considerations and methodology. The successful applicant will take a lead role in development and application of models and contribute to a broader portfolio of projects through regular participation in working groups. Candidates must have a PhD in Health Policy, Health Economics and Outcomes Research, Statistics, Computer Science or related field and a strong background in computational techniques and programming.

The expected pay range for this position is $84,500 to $118,000 per annum.

Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at stanfordelr@stanford.edu . For all other inquiries, please submit a contact form.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at stanfordelr@stanford.edu . For all other inquiries, please submit a contact form.

Stanford is an equal employment opportunity and 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, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research mission.

REQUIRED:

•Ph.D. in Health Policy, Health Economics and Outcomes Research, Statistics, Computer Science or related field.

•Strong background in mathematical/statistical or computational techniques.

•Strong programming skills in R, Python or other languages.

•Experience in developing simulation models required.

•Ability to work independently and under deadlines is essential.

•Excellent organizational skills and demonstrated ability to complete detailed work accurately and thoroughly.

•Ability to work collaboratively as a member of a research team.

DESIRED:

•Training in medicine, biology or public health.

•Interest in health policy and public health.

•Prior experience in collaborative empirical research.

Additional Information

• Schedule: Full-time

• Job Code: 6784

• Employee Status: Regular

• Grade: R99

• Requisition ID: 103176

• Work Arrangement : On Site