The Empirical Study of Conflict (ESOC) Project seeks a Research Specialist to provide geo-spatial and statistical analysis as well as qualitative research for a multi-university team of researchers. Under the direction of the Principal Investigator, the Specialist will analyze and develop micro-level conflict data to examine politically motivated violence worldwide and the efficacy of policies to reduce it (including Afghanistan, Colombia, India, Iraq, Pakistan, and the Philippines).
This position is ideal for those with Master's degrees seeking an applied research position as well as exceptional graduating seniors with a strong interest in pursuing a PhD in Economics or Political Science after acquiring applied research experience.
This is a one-year position. Extension may be possible. Applications will be reviewed on a rolling basis.
Applicants should submit a cover letter and C.V. online. Upon request, candidates should be prepared to submit references, transcripts, and/or writing samples.
- Develop and analyze micro-level conflict data to examine politically motivated violence worldwide.
- Analyze the efficacy of policies to reduce the violence worldwide.
- BA or more advanced degree, preferably in social science or statistics, or equivalent work experience
- Academic experience conducting micro-economic and statistical analysis
- Proficiency with or ability to rapidly learn R or STATA, Python and QGIS software or equivalent
- Excellent writing and analytical skills
- Evidence of ability to take the initiative in solving practical research problems
- Ability to work independently and to adjust to rapidly changing needs of researchers
- Two years or more experience working on applied machine learning projects.
- Candidates are expected to be familiar with data munging tasks such as transformations, visualizations and mining. Familiarity with popular data cleaning libraries (e.g. tidyverse, pandas) and geographic packages (e.g. sf, stars, geopandas, rasterio) in R and/or Python.
- Master’s degree in Data Science, Economics, or Statistics or related discipline
- Experience with impact evaluation projects involving randomized trials, matched control designs, or observational data. Need not be in an academic setting.
- Experience with automated scraping of data from websites or use of API calls
- Familiarity with high-performance computing, or writing parallelized code. Experience with larger-than-memory operations is a plus. Experience using command line on Linux, Unix, or WSL machines.
- Familiarity or willingness to learn data visualization, especially for geospatial data
- Exposure to machine learning techniques, with a preference for candidate who have used ML algorithms in research settings
We at the School of Public and International Affairs believe that it is vital to cultivate an environment that embraces and promotes diversity, equity and inclusion — fundamental to the success of our education and research mission. This commitment to diversity informs our efforts in recruitment and hiring as we actively seek colleagues of exceptional ability who represent a broad range of viewpoints, experiences and value systems, and who share Princeton University's dedication to excellence.
Princeton University is an Equal Opportunity/Affirmative Action 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. EEO IS THE LAW
Standard Weekly Hours36.25Eligible for OvertimeYesBenefits EligibleYesProbationary Period90 daysEssential Services Personnel (see policy for detail)NoEstimated Appointment End Date12/1/2022Physical Capacity Exam RequiredNoValid Driver's License RequiredNo#LI-NC1