Sort by
Refine Your Search
-
addition to pursuing their own research agenda, we seek applicants with experience in survey design and computational methods, and working with complex large-scale data. Successful candidates will have completed a Ph.D
-
PhD with an interest in computational social science or data science (broadly defined). This individual will help design, execute, and analyze a series of field experiments on a platform created by the
-
: Leveraging big data and computational methods to analyze adaptation behaviors and incorporate its costs and benefits into climate impact assessments. • Adaptation of Places: Partnering with natural scientists
-
working in large teams with diverse disciplinary, sectoral, and cultural backgrounds; o For those experts in qualitative data, qualitative data experience and analytical skills are considered an asset. Duke
-
. The preliminary description of the research project is: Increases in the size, frequency, and severity of wildfires are driving large-scale conversion of forests to shrublands across the western U.S. Despite
-
Duke University Department of Obstetrics and Gynecology has an immediate opening for a Postdoctoral Associate in the Division of Reproductive Sciences. More information about this division is located
-
with our co-PI at UCLA. Responsibilities include study design, supervising and leading data collection, coding, and analysis, and writing of manuscripts for publication, as well as grant preparation
-
inference and large-scale data sets. - Experience working in interdisciplinary or applied research settings involving policy, planning, or external partners. PROGRAM DETAILS & BENEFITS: This is a full-time
-
for projects examining questions in cardiovascular disease using extremely large data sets comprised of routinely-collected clinical data · Developing and maintaining requirements for access to Truveta Data and
-
interventions and “nudges” in collaboration with external partners (e.g., companies, nonprofits, policy organizations) • Using advanced data analysis methods to extract interpretable patterns from large, messy