The Department of Epidemiology and Biostatistics at Temple University College of Public Health seeks a talented, highly motivated, and self-driven researcher with a background in epidemiology, biostatistics, applied mathematics, or other related social/behavioral science to work with Dr. Brandie DePaoli Taylor and Dr. Abby Rudolph. The College of Public Health is fully accredited by the Council on Education in Public Health as a school of public health and enrolls nearly 5,000 students in 8 undergraduate and 28 graduate degree programs. The College has experienced remarkable growth and organizational expansion in the educational programs offered, research activities supported by NIH, NSF, and other major funders, and interdisciplinary collaborations. Researchers at the College are actively engaged in projects which focus on social, behavioral, and environmental inquiries, medical/health interventions, and basic science and are sponsored by NIH, NSF and other major funders. Temple is an urban, research-intensive R1 university located in Philadelphia, a city rich in history, culture and diversity.
The post-doc will primarily work on two projects and will be expected to produce peer-reviewed publications and presentations at scientific meetings.
The first project will involve conducting analyses that incorporate census track level data, sexual risk behaviors, substance use, socioeconomic status, and mental health indicators to measure syndemic risk clusters for sexually transmitted infections in youth and young adults. This National Center for Health Statistics (NCHS) approved project will utilize restricted access data from the National Health and Nutrition Examination Survey (NHANES) through the Philadelphia Federal Statistical Research Data Center. Various approaches including latent class analyses, regression trees and structural equation modeling will be implemented to determine gender and race/ethnic specific risk profiles for sexually transmitted infections.
The second project will involve conducting analyses to understand the independent and joint contribution of social network and neighborhood/spatial factors on voluntary drug treatment enrollment, use of harm reduction services, and other health-seeking behaviors among persons who use drugs and/or who are living with HIV/AIDS. Spatial analyses will involve defining activity spaces, computing road network distances (miles and minutes) using varying modes of transportation, location-allocation models, and joining individual-level data with neighborhood and census data sources. Network analyses will include egocentric, sociometric, and dyadic analyses.
- Completion of a PhD (in a health-related field), DrPH, MD, DVM, DDS, or similar doctoral degree
- Research experience in the social sciences
- Prior coursework in statistics, GIS, and epidemiology
- Experience with statistical software packages (e.g., SAS, STATA, R) to manage and analyze quantitative data and with ArcGIS, QGIS, or R for spatial analyses
- Ability to conduct descriptive and complex statistical analyses, latent class analysis, regression trees, and to develop multivariable statistical models
- Prior experience working with national data sets
- Excellent communication skills, both oral and written, demonstrated through the development of publications and delivery of presentations
- Ability to work well independently, and as part of a team
- Ability to handle confidential materials with discretion
This position will provide postdoctoral research training, funds for travel to conferences for research dissemination and professional development, and a competitive salary and benefits for one year, renewable for a second year upon satisfactory performance. The fellow will be expected to learn new research skills, develop independent avenues of research, participate in interdisciplinary team science, and publish research findings.
Strong applicants will demonstrate evidence of scholarly potential that will make them competitive for tenure-track appointments at a research university. Interested candidates should send a CV, cover letter summarizing relevant training and research experiences, two publications (or representative writing samples), and the names of 3 references to firstname.lastname@example.org and email@example.com.
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