Computational Researcher Jobs (NOW HIRING)

Profs. Sam Wang and Simon Levin perform research on aggregated decision-making through rule systems. This work includes research into electoral mechanisms including the voting rules, redistricting, and Electoral College. As part of these efforts, they are recruiting a Computational Research Analyst.

The Computational Research Analyst will develop computational analysis of redistricting and voting rules, toward the goal of performing analytics and scholarship relevant to identifying the performance characteristics and inefficiencies of complex U.S. election systems. A main focus is translating the dimensionality of aggregated cognitive approaches of large populations of voters to their ballots, with the goal of going from modeling all the way to practical interpretability. The work will be made publicly available through peer-reviewed scientific scholarship as well as databases that may be of use to a variety of audiences.

The work will include dissemination and archival of codebooks, scripts, map content, and analytics. Other work includes the investigation of electoral rules such as ranked-choice voting and other modifications, with the goal of quantifying functional impacts. Translation to general audiences is part of the work and will produce content that is understandable to nontechnical readers (for example see one publication, the Princeton Gerrymandering Project). This comes in addition to other scholarship in scientific, statistical, and law journals.

This position is suitable for someone with graduate or postgraduate level competence in one or more relevant subject areas, including computational simulation, model testing, and geospatial analysis.

The term of this appointment is 1 year, with the possibility of renewal based upon satisfactory performance and funding.

• Perform original computationally intensive research on ranked-choice voting and other proposed changes to U.S. electoral institutions.
• Maintain and expand a high-quality database of computationally driven analysis of redistricting plans for all 50 states combining census data, precinct-level results, and other information using Python (including numpy) and GIS software.
• Publish codebooks and datasets to allow public access to analysis, and to drive legal and academic scholarship.
• Coordinate with collaborators in several states.

Essential Qualifications:

• This position requires a Bachelor's degree in Computer Science, Statistics, or related quantitative discipline and 1+ years of experience.
• Strong quantitative and programming background (Python, QGIS)
• A willingness to learn GIS software and other programs or tools necessary for the project
• Experience gathering and combining data from many disparate sources
• An interest in law, government, or democratic reform
• Ability to balance and work on several projects simultaneously and successfully
• Strong orientation toward teamwork and collaborative research

Preferred Qualifications:

• Background in high-performance computing (C, C++, or a comparable language) is a plus.
• Excellent writing and verbal presentation skills are also highly desired.

Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.

The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.

If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.

The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.