The Division of Primary Care and Population Health seeks to serve our community through caring, learning, and innovation for the whole person through all stages of life. While engaged in practice and teaching, our faculty are dedicated to establishing new knowledge as the basis for future practice and prevention, and to the greatest extent possible applying that knowledge to improve care for all and reduce health disparities.
The research scholar will take a leadership role in Pascal Geldsetzer’s research group, which is a “dry lab” focused on quantitative analyses of existing, and often publicly accessible, datasets. The group is currently focused on studying the causal effect of shingles vaccination on cognition. In extensions of this work, the group is also interested in the effect of other vaccinations given in old age on dementia as well as the effect of infections on dementia. Key data sources for our projects are electronic health record data, epidemiological cohort studies, mortality data, and other large health-related administrative datasets. The researcher will be expected to publish in high-impact peer-reviewed journals.
We are in particular looking for individuals with in-depth experience in econometric/quasi-experimental approaches for causal effect estimation (e.g., regression discontinuity and difference-in-differences). We are looking for someone to start as soon as possible but there is no specific deadline for the application – we hire on an ongoing basis.
The initial appointment will be 1-year fixed term. The fixed-term may be renewed for additional years based on business needs.
CORE DUTIES:
- Carrying out data analyses
- Supervising data analyses led by graduate students and postdoctoral fellows
- Writing manuscripts for publication in scientific journals
- Mentoring and advising junior researchers
- Assisting with, and leading the writing of, grant applications for research funding
- Communicating with research funders, data providers, and project administrative staff
EDUCATION & EXPERIENCE:
• Doctoral degree with quantitative training or research experience.
• Training and experience in quasi-experimental techniques (regression discontinuity, difference-in-differences, interrupted time-series, etc.)
• A background in health-related research is a plus but not required
KNOWLEDGE, SKILLS AND ABILITIES:
• Strong coding skills in R, Stata, or other statistical software package.
• Strong writing and analytical skills.
• Ability to prioritize workload.
This role is open to candidates anywhere in the United States.
Why Stanford is for You
Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:
- Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
- A caring culture. We provide superb retirement plans, generous time-off, and family care resources.
- A healthier you. Climb our rock wall or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
- Discovery and fun. Stroll through historic sculptures, trails, and museums.
- Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more.
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
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.
