Overview
The IAEA is seeking an intern to apply modern remote sensing and imagery science techniques to satellite imagery and geospatial information, contributing to the development of value-added tools for imagery analysts.
Tasks Summary
- Building rapid prototypes and Proof of Concepts (PoC) to determine fit and usability
- Interacting with business users to define the scope and analytics business case
- Supporting in the development and application technologies such as machine-learning and deep-learning algorithms to enable imagery and geospatial analytics product functionality
- Identifying suitable open-source imagery and geospatial data sources and implementing related data collection, cleaning, pre-processing, and labelling processes.
Experience Requirements
- Basic familiarity with computer programming and satellite imagery analysis is an asset.
- Foundational proficiency in Python programming for data analysis, image processing, or geospatial applications with the ability to write clear, well-structures scripts or notebooks.
- Exposure to machine learning concepts and libraries commonly used for image and geospatial data (e.g., PyTorch, TensorFlow, scikit-learn) including coursework, projects or research experience.
- Basic knowledge of remote sensing and satellite image processing, including familiarity with common data formats (e.g., GeoTIFF) and Python-based geospatial or image processing libraries (e.g., GDAL, rasterio, NumPy) gained through academic or project work.
- Understanding of machine learning methodologies applied to imagery such as supervised and unsupervised learning and introductory deep learning concepts (e.g., convolutional neural networks) demonstrated through coursework or practical projects.
- Awareness of multi-resolution and multi-sensor data challenges, including spatial resolution differences, co-registration, and resampling, particularly in the context of combining high-resolution imagery with lower-resolution multispectral data is an asset.
Qualification Requirements
University degree in mathematics, statistics, remote sensing, or a data science related field.
