Project Overview

We are looking for a highly motivated and innovative Research Intern to join our team in advancing research in the field of sustainable urban development and computational social science. 

This internship offers a unique opportunity to gain hands-on experience in mining large-scale datasets and developing data-driven analyses to enhance our understanding of the relationship between ecological awareness, office environments, and career trajectories.

Responsibilities

Assist in cleaning, processing, and analysing two large-scale datasets: LinkedIn data and LEED certification data for office spaces across various companies.

Contribute to the development of data-driven methods, including causal inference analysis and network-based models, to track mobility patterns across office spaces.

Participate in technical discussions, research meetings, and brainstorming sessions.

Requirements

Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Mathematics, Quantitative Economics, Urban Planning, or a related field.

Proficiency in Python and R, with experience in large-scale data mining.

Strong analytical and problem-solving skills, with the ability to derive insights from complex datasets.

Ability to work effectively in a collaborative, multidisciplinary environment.

A keen interest in data-driven urban research and computational social science.

This internship is only open to full-time matriculated or registered students in the six autonomous universities Singapore. The internship must be approved by the University.