*************************** Student Hourly Worker Opportunity! ***************************
Hours of work: 10 hours per week over 23 weeks
Hourly rate: $26 per hour

Position Summary:
This graduate research assistant will support an interdisciplinary, multi-university project titled, “From
Obstruction to Opportunity: Renewable Energy Transitions and the US Agricultural Sector”.

Project Description:
While previous research explores how agricultural organizations have lobbied to obstruct action on
climate change, limited research examines the role of the agricultural sector and land ownership in
national and local transitions to renewable energy. The widespread practice of siting utility-scale wind and
solar projects on farmland creates opportunity for new sources of revenue. However, the expansion of
wind and solar is hampered by substantial obstacles around siting, including local opposition near
planned sites, idiosyncrasies in local government decision-making, and dynamics of land ownership.
Increasing consolidation within the agricultural sector further complicates equitable distributions of power
and decision-making. This project investigates the role of the agricultural sector in obstructing or
supporting RE developments through siting needs, land use decisions, and its role in shoring up public
support or opposition for such projects. Through this work, we identify the distributional and equity
implications of RE siting on agricultural land in the path to decarbonization.

Position Assignment:
● Collect, clean, and merge data on large-scale solar projects in the US, land ownership, and
socio-demographics (e.g. Census data, USDA data).
● Work with the project team to analyze and visualize these patterns in land ownership,
socio-demographics, and other explanatory variables.
Be registered in a graduate program at Rutgers University, preferably in planning, public policy,
geography, or another environmental social science program.

Preferred qualifications:
● Strong quantitative/computational social science skills (including statistics, econometrics, causal
inference, etc.)
● Proficiency in a programming language, preferably R (or STATA)
● Strong GIS and spatial analysis proficiency
● Experience with collecting, merging and managing large quantitative datasets
● Interest in climate change and energy transition issues preferred

To apply:
Send a short cover letter, resume, and related spatial or quantitative work sample (e.g., class assignment)
to Professor Mark Paul (mark.paul@rutgers.edu).

In your brief cover letter, please be sure to outline the reasons why you are interested in this position, relevant experience and knowledge, and your availability. Applications will be reviewed on a rolling basis until the position is filled.

To apply for this job email your details to mark.paul@rutgers.edu