Career Opportunities with FFCWS

Research Software Engineer

The Center for Research on Child Wellbeing (CRCW) at Princeton University is seeking a Research Software Engineer to collaborate on research and provide computational expertise in data engineering, applied machine learning, and optimization in order to create efficient and scalable research code. This position will have a significant role in designing and conducting additional research building on the Fragile Families Challenge. This position will work with the project Principal Investigator (Matthew Salganik) and will contribute to the research community at Princeton, including the community focused on the Fragile Families and Child Wellbeing Study (FFCWS).

The ideal candidate will have a strong background in statistics, machine learning, and data engineering. They will be able to translate academic research into production quality, stable and documented code.

For more information on the responsibilities and qualifications, and to apply for this position, please visit the job listing on the Careers at Princeton website.

 

Research Assistant – State Policy Variation & Family Wellbeing Project

Seeking part-time, 1 day a week, assistance on a project which aims to understand whether state-level policy conditions aid or limit families’ abilities to recover from economic downturns. This project entails creating a new state policy variation database to append to the Fragile Families and Child Wellbeing dataset – a longitudinal birth cohort of children born in large U.S. cities between 1998 and 2000 – and examining which sets of policies are most beneficial for families’ economic wellbeing and for which families these policies are most important.

Research assistant tasks will include creating a database of state-level policies, documenting sources for all state policy data, data cleaning, and longitudinal data analysis. There is the potential to co-author peer-reviewed publications.

The successful candidate will have experience working with longitudinal data and advanced statistical analysis, be proficient in Stata and Microsoft Excel, and, preferably, have completed coursework in social policy.

Please apply by submitting a CV/resume and cover letter to Kris McDonald (kemerson@Princeton.EDU).