Intern (ERDI-ERDD) 2601-009

6. Education Requirements

• Currently enrolled in a masters degree or PhD program in Data Science Computer Science Environmental Science Economics Econometrics or related fields.

• Completed graduate-level coursework in data analysis statistics machine learning and/or environmental science

7. Relevant Experience and Other Requirements

• Experience in programming languages
• Strong analytical skills
• Ability to work independently and as part of a team
• Interest in environmental issues and a desire to make a positive impact
• Preferable with 2-3 years relevant professional experience.
• Excellent oral and written communication skills in English

Economic Research and Development Impact Department (ERDD)

Data Division (ERDD)

1. Internship Topic

Big data and spatio-temporal dynamics between human activities and the environment

2. Summary of Job Description

The intern will

• Focus on extending a big-data methodology to a new geographic region to study the spatio-temporal dynamics between human activities and the environment.
• Involve processing and integrating large-scale geospatial datasets such as mobile device location data vessel AIS data and satellite-derived environmental variables ranging from hundreds of gigabytes to terabytes.
• Conduct research that aims to adapt and optimize an existing analysis pipeline for regional generalization with an emphasis on improving computational efficiency tuning key hyperparameters and packaging the workflow into a reusable Python tool. By applying advanced signal processing and machine learning techniques the project seeks to derive actionable insights into how human behaviors and environmental systems interact across space and time.
• Replicate and extend big-data research methodology to study human-environment interactions in a new region.
• Analyze model outputs and derived data to validate findings interpret patterns and draw conclusions about regional human-environment dynamics.
• Contribute to the development generalization and documentation of a reusable Python package to facilitate future research.
• Synthesize and report findings to project consultants and supervisors through regular updates and presentations.
• Author a complete technical paper detailing the methodology results and implications of the replication study for publication or internal dissemination.
• Perform any other tasks assigned by the supervisors.

3. Period of Assignment

Duration: 11 weeks

Timing: June 2026 onwards

4. Location

ADB Headquarters Manila Philippines

5. Expected Outcomes

• Validated Generalization of a Big-Data Methodology

• Development of a Reusable Research Tool

• High-Quality Technical Documentation and Insights

• Enhanced Methodological and Professional Skills