The Social & Decision Analytics Division (SDAD) is seeking applications for multiple postdoctoral associates in statistics and social and behavioral sciences. SDAD is a leading laboratory in the Biocomplexity Institute & Initiative (BII) at the University of Virginia. BII performs world-class informatics research in life sciences, social sciences, and human health by integrating theory, modeling and simulation with computational and experimental science in a transdisciplinary, team science research environment.
SDAD combines expertise in statistics and social and behavioral sciences to develop evidence-based research and quantitative methods to inform policy decision-making and evaluation. The researchers at SDAD span many disciplines including statistics, economics, computational social science, psychology, political science, policy, and program evaluation, and data science. SDAD methods integrate statistical learning, network science, cognitive science, behavioral economics, game theory, crowdsourcing, and machine learning.
SDAD researchers address complex social problems by leveraging the diversity of data flows available today including administrative and government records, surveys, social media, and sensors. Through team collaboration, the postdoctoral candidate is expected to develop the capacity to discover, repurpose and redirect these data flows to solve critical social problems. Computational complexity is at the heart of SDAD research and SDAD leverages all the research capability of BII, along with the High Performance Computing infrastructure.
The position will be offered at the rank of postdoctoral associate and will be located in BII's location in Arlington, VA. Position reports to Sallie Keller, Director of SDAD and Professor of Public Health Sciences. The anticipated start date for the position is May of 2019.
Applicants must be on track to receive a PhD in statistics, social and behavioral sciences, digital humanities or in a very closely related field by May of 2019 and must hold a PhD at the time of
Willingness to work in a team science
Experience with advanced approaches to statistics and data-driven model
Experience with statistical software systems such as R, programming, and
Excellent communication skills, both oral and written, demonstrated through the development of publications and delivery of
Be motivated, enthusiastic and self-driven.
Ability to excel in a highly collaborative team science
Preference will be given to those applicants with:
Experience using diverse sources of data, both traditional ones such as surveys, and non-traditional ones, such as administrative data and social
Internal Number: 0624562
About University of Virginia, Social & Decision Analytics Division, Biocomplexity Institute
The Biocomplexity Institute & Initiative at the University of Virginia integrates scientific research – from genetic sequencing to policy analysis – to tackle the complex task of understanding massively interacting systems and predict solutions to issues impacting human health, well-being, and habitat.
As pioneers in biocomplexity, we understand that interactions at the micro level can produce significant effects on the macro scale. We collaborate across many disciplines to discover connections between health, information networks, security and infrastructure.
The foundation of our methodology lies in information biology; the synthesis of mathematics, computation, informatics, and biology. We approach complex problem solving by assembling teams of experts in a variety of fields to work together to create solutions that challenge the very fields in which the teams operate.
The Social & Decision Analytics Division consists of statisticians, social scientists, and behavioral scientists who use big data to develop evidence-based research and use quantitative methods to improve the impact of policy decisions.