Postdoctoral Research Associate I, Psychology (Genetically Informed Studies of Social Connectedness)

The University of Arizona's Department of Psychology invites you to apply for the role of Postdoctoral Research Associate I. This postdoctoral fellowship position is funded by NIA grant (#AG078361-01), Genetically Informed Studies of Social Connectedness and Health, awarded to Dr. David Sbarra (PI) at the University of Arizona. The grant is a collaborative study with the Washington State Twin Registry (WSTR), which is among the most active twin registries in the United States.

Our postdoc position affords incredible research opportunities in areas related to the behavior genetic study of social relationships and health. The study involves a complex and sophisticated data collection spanning detailed neuropsychological assessments, the quantification of biological aging, and cutting-edge ambulatory assessments of daily social experience.

We are interested in hiring a person with a strong background in behavior genetics but will consider any applicant with demonstrated experience with advanced statistical methods, including a focus on causal inference, bioinformatics and computation (more broadly), or other cutting-edge analytic tools.

Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; access to U of A recreation and cultural activities; and more!

The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.

• Contribute to NIH-funded research, including but not limited to assisting in data management, data curation and pre-registrations, data analysis, and manuscript drafting.
• Contributing to activities in the PI's laboratory that support the parent project, including but not limited to maintaining and developing a bioinformatics pipeline for the quantification of epigenetic aging metrics.
• Contribute to collaborating on the supervision of graduate and undergraduate students working on the parent project.

Knowledge, Skills, and Abilities (KSAs) for the Ideal Postdoctoral Candidate Include:

• Demonstrated strengths as a data analyst, especially with complex biometric twin or bioinformatics, or molecular genetic data.
• Advanced knowledge of the statistical software package R.
• Interest in statistical methods for causal inference.
• Knowledge of research findings in epigenetic aging.
• Collaborative, generous, curious, and humble scientific spirit.
• Effective communication in and around lab environments.
• A commitment to open and reproducible science.
• Strong and demonstrated leadership skills.

• Ph.D. in a relevant field completed or expected to be completed at the time of hire.
• Experience in advanced data analysis.
• Familiarity with the computational methods for the analysis of methylation-based array data, including epigenetic clocks, and/or familiarity with co-twin behavior genetic methods.