Please email materials to Ms. Anna Lue, firstname.lastname@example.org. Applications received before July 1, 2019 will be given priority, but applications will be accepted until the position is filled. Anticipated start date is early fall 2019 but is flexible.
Post-Doctoral Fellowship in Maternal and Perinatal Health at Stanford University School of Medicine
We are seeking an individual with training and experience in epidemiology or a related field (PhD or PhD/MD) for a postdoctoral fellowship related to maternal and perinatal health; the primary mentor is Professor Suzan Carmichael. This postdoctoral research position will be focused primarily on maternal health outcomes in the United States, with a particular emphasis on severe maternal morbidity, maternal nutrition and weight, health care, social disadvantage, and/or disparities. The postdoc will have the opportunity to collaborate with a variety of epidemiologists, physician-scientists, biostatisticians, and social scientists at Stanford University as well as other institutions. The postdoc will be located at the Stanford School of Medicine and have opportunities to be involved with a variety of other groups at Stanford such as the California Maternal Quality Care Collaborative (CMQCC), the California Perinatal Quality Care Collaborative (CPQCC), the Center for Population Health Sciences, the Center for Policy, Outcomes and Prevention (CPOP), and the March of Dimes Prematurity Research Center.
Faculty Sponsor: Suzan Carmichael, PhD, MS
Department of Pediatrics (Neonatology)
Department of Ob/Gyn (Maternal-Fetal Medicine and Obstetrics)
Department of Health Research & Policy, by courtesy (Epidemiology)
Fellow, Center for Population Health Sciences
Stanford University School of Medicine, Stanford, CA
- The ideal candidate will be interested in an academic research career conducting epidemiologic research related to reproductive, maternal, and infant health outcomes, and be highly motivated to make a difference in maternal and perinatal health.
- Training and experience in epidemiology or a related field (PhD or PhD/MD).
- Familiar with statistical software, (e.g., SAS, R).
- Strong training in quantitative epidemiologic methods (e.g., causal inference methods, Bayesian methods).
- Strong written and interpersonal communication skills.
- Applicants need not have completed their doctoral training prior to applying, although training must be completed prior to the start of the fellowship.
- Curriculum vitae
- A cover letter describing research interests to be pursued during training
- One lead-author published or unpublished manuscript
- Names of two references