Social Science Research Scholar (1-year Fixed Term)

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 live. 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: Carring 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 Qualifications:

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. #J-18808-Ljbffr Stanford University