The successful candidate will work with a team of researchers from the Bloustein School’s Planning Program on an externally funded project examining the state of affordable rental housing in New Jersey. This project involves creating a data infrastructure for understanding the existing landscape of affordable rental housing across the state; conducting interviews and focus groups with a range of organizations and renters to shed light on issues confronting renters across a spectrum of population subgroups, housing stocks, and geographic areas; producing tools, reports, and other deliverables; and convening conferences and trainings to solicit feedback on interim materials, demonstrate the application of tools and other outputs, and disseminate research findings.

Specific postdoc duties will include working with the research team to collect and analyze quantitative data related to rental housing, including:

  • Federal, state, and local records of subsidized households and housing units
  • State tax records indicating type, ownership, and location of rental properties and units
  • The relationship between municipal rent regulation ordinances and the rental stock that is and is not covered by them
  • Census data for the study of the relationship between neighborhood dynamics and the characteristics of the rental stock in areas experiencing change


  • Fluency in data cleaning and analysis in a programming language, with a preference for Python and/or R
  • Strong organizational skills and exceptional attention to detail; the successful candidate will record and share detailed accounts of their efforts (analysis steps, etc.) and participate in regularly scheduled research team meetings
  • Strong written communication skills; the successful candidate will be involved in producing written reports summarizing research findings and describing research materials and methodology.


  • Domain expertise in housing and urban research, with experience working with longitudinal data
  • Experienced with advanced statistical analysis
  • Preference for those fluent in R, Python, Stata (R highly preferred)
  • Ability to analyze data and produce maps using software for spatial analysis, particularly ArcGIS and/or QGIS

Prior to being hired, candidates shall have completed all requirements for a PhD in public policy, planning, geography, demography, or a related field.

Under Policy 60.1.35, Rutgers University requires all prospective employees to provide proof that they are fully vaccinated and have received a booster (where eligible) against COVID-19 prior to commencement of employment, unless the University has granted the individual a medical or religious exemption.

To apply: