Lab Assistant in AI/ML/Spatial Data Science for Global Development (Graduate Level, Data Science, Social Work) Rutgers University in United States

Rutgers University School of Social Work is seeking a Lab Assistant for a graduate-level course and research in AI, machine learning, and spatial data science for global development and social policy. The position is ideal for candidates with a Master's or Ph.D. and strong experience in data science, unstructured data, and machine learning. Required skills include advanced Python programming, with additional experience in ArcGIS or QGIS considered a plus. The role involves supporting a programming lab component, working on data-intensive projects, and potentially contributing to curriculum planning. The stipend is $3,250 or higher for approximately 5 hours per week.

The associated Ph.D.-level course introduces students to applied data science for global development, using spatial data sources such as satellite imagery, crowd-sourced maps, and social media data. Students will learn to apply AI/ML methods to measure poverty, food security, and access to services, supporting policy design and evaluation. The course is interdisciplinary, welcoming students from social work, public policy, international development, computer/data/information science, economics, statistics, business management, and geography. Project teams will develop policy-relevant research projects, with each team working towards a conference paper draft.

Applicants should have prior coursework in statistics and experience with statistical software or programming languages (Stata, R, Python, MATLAB, ArcGIS). Strong communication and computer skills are essential. The position offers exposure to cutting-edge applications of data science in global development and social policy, with opportunities for hands-on research and collaboration.

To apply, send your CV to Dr. Woojin Jung at [email protected]. For course registration, students from other departments may enroll with the instructor's permission. For more information, refer to the provided links or contact the supervisor directly.