Position Overview
The Cooperative Institute for Satellite Earth System Studies (CISESS) at the University of Maryland is seeking a motivated Scientific Software Developer for a two-year project supporting PrecipWatch, a web-based platform for satellite precipitation data processing, visualization, and analysis.
Besides producing several precipitation products in near-real-time, PrecipWatch also provides a unified, interactive interface for displaying and analyzing precipitation products from multiple satellite and radar-based sources, including NOAA’s Microwave Integrated Retrieval System (MiRS), Enterprise Microwave Rain Rate and Type (EMRRT), Snowfall Rate (SFR), CMORPH2 blended precipitation analysis, Enterprise Rain Rate (ERR), and Multi-Radar/Multi-Sensor System (MRMS). An initial demonstration system has been developed using Python, Flask, JavaScript, and OpenLayers. The selected candidate will continue developing the existing platform, improving processing efficiency, and expand its visualization and data integration capabilities.
Key Responsibilities
- Develop and maintain Python-based scientific data processing pipelines for satellite precipitation products.
- Process NetCDF, HDF, and geospatial datasets into web-compatible raster tiles and GeoJSON layers.
- Develop and enhance interactive web applications using JavaScript, HTML, CSS, and model web frameworks.
- Improve satellite swath visualization, map rendering, and data processing performance.
- Develop backend services and REST APIs using Python-based web frameworks.
- Implement interactive visualization features, including animations, timelines, data queries, and precipitation product comparisons.
- Support automated data processing, expanded historical data coverage, and near-real-time data updates.
- Collaborate with NOAA and university scientists on scientific software development, testing, and documentation.
Required Qualifications
- Bachelor’s or master’s degree in Computer Science, Software Engineering, Atmospheric Science, Earth Science, Engineering, or a related field.
- Strong programming skills in Python.
- Experience with web programming languages, including JavaScript, HTML, and CSS.
- Familiarity with scientific data processing, data visualization, or web application development.
- Strong problem-solving, debugging, and communication skills.