Remote Sensing for Time Series Data Processing Internship

About Internship

Assistant Professor from Indian Institute of Technology - Indian School of Mines, Dhanbad (IIT-ISM Dhanbad), is accepting interns interested in the field of Earth Planetary Sciences, in the research area of Artificial Intelligence and Machine Learning.

This internship focuses on large-scale satellite time series data acquisition and preprocessing for AI/ML-based environmental analysis. The work involves automated downloading of multi-sensor satellite datasets, performing atmospheric and radiometric corrections, cloud masking, and harmonization of imagery for downstream machine learning applications. The role integrates geospatial data engineering with AI-driven analysis in Earth system studies. Master’s or Ph.D. in Remote Sensing, Geoinformatics, Geography, Environmental Science, or a closely related field can apply. Key Responsibilities: 1. Downloading and managing satellite time series datasets from platforms such as USGS EarthExplorer, ESA Copernicus Hub, NASA LP DAAC, and NOAA CLASS 2. Developing automated data retrieval workflows using Python/R scripts and APIs 3. Performing atmospheric correction, radiometric calibration, and geometric correction 4. Implementing cloud masking, gap filling, and multi-sensor data harmonization (e.g., Landsat, Sentinel, MODIS) 5. Resampling, reprojection, and mosaicking large satellite image collections 6. Utilizing tools such as Google Earth Engine (GEE), SNAP, QGIS, ENVI, and GDAL-based Python libraries 7. Supporting scalable geospatial processing workflows for AI/ML model development Learning Outcomes: 1. Gained expertise in satellite time series data handling and preprocessing pipelines 2. Developed automation workflows for large geospatial datasets 3. Strengthened programming skills in geospatial data science (Python/R) 4. Integrated remote sensing preprocessing with AI/ML-based environmental modeling 5. Acquired practical exposure to cloud-based and large-scale Earth observation data systems