Post-Doctoral Researcher - Civil & Construction Engineering - Hydroinformatics and Global Hydrologic Forecasting

Brigham Young University • Provo, UT

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About The Position

The Post-Doctoral Researcher will support advanced technical and research activities for the GEOGLOWS (Global Earth Observation for Water Sustainability) initiative with a primary focus on hydrologic modeling systems, cloud-based data infrastructure, and applied hydroinformatics. The position will work closely with the GEOGLOWS technical lead to advance core system capabilities, support partner integrations, and translate research innovations into operational, globally scalable services. This role emphasizes technical depth, software engineering rigor, and applied research, serving as a key contributor to system development, validation, and deployment across international partners.

Requirements

• PhD in Civil Engineering, Hydrology, Water Resources, Computer Science, or a closely related field. The required degree must be completed by the start date.
• Strong background in hydrologic modeling, hydroinformatics, or environmental data science.
• Demonstrated experience developing scientific or engineering software in Python or similar languages.
• Experience working with large geospatial or time-series datasets.
• Excellent written and verbal communication skills in English.

Nice To Haves

• Experience with cloud computing platforms (AWS and/or Google Cloud Platform).
• Familiarity with global or continental-scale hydrologic models (e.g., GEOGLOWS RFS, NOAA National Water Model).
• Experience with hydrologic data services such as HydroShare, HydroServer, or WMO-aligned systems.
• Prior work on open-source software projects and collaborative code versioning (e.g., Git/GitHub).
• Interest in applied research with international partners and real-world decision-support contexts.
• Experience with or interest in AI/machine learning applications in hydrology or environmental science.

Responsibilities

• Hydrologic Modeling & Forecast Systems Support the ongoing development, testing, and enhancement of the GEOGLOWS Global River Forecast System (RFS), including Version 3 upgrades and experimental workflows.
• Contribute to model evaluation, validation, and uncertainty analysis in collaboration with international datasets and partner institutions.
• Assist with integration of additional hydrologic components such as baseflow separation, groundwater and GRACE-based products, and long-range forecasting extensions.
• Technical Development & Cloud Infrastructure Design and implement software tools and workflows for hydrologic data processing, analysis, and visualization using Python and related scientific computing libraries.
• Support cloud-based deployment and data distribution strategies using AWS and Google Cloud Platform resources, including open-data programs and scalable APIs.
• Contribute to interoperability efforts between GEOGLOWS, and other external data providers, with emphasis on enabling communities to contribute shared data that improves both the RFS and partner other potential models.
• Applied Research & Innovation Conduct applied research that bridges hydrologic science with operational forecasting, decision-support tools, and real-world implementation in areas such as flood early warning and flood inundation modeling.
• Codify and advance technical standards for hydrologic data sharing, reproducibility, and GEOGLOWS workflows, drawing from the existing RFS to make model outputs more accessible, interoperable, and able for other model providers to follow.
• Co-author peer-reviewed journal articles, technical reports, and conference presentations related to global hydrologic forecasting and hydroinformatics.
• Collaboration & Mentorship Provide technical guidance to graduate and undergraduate students contributing to GEOGLOWS-related research and software development.
• Collaborate with interdisciplinary team members and external partners working on validation, impact analysis, and regional implementation while maintaining a primary focus on technical contributions.
• Support documentation, tutorials, and internal knowledge transfer to ensure continuity and scalability of technical systems.

What This Job Offers

• Job Type: Full-time
• Education Level: Ph.D. or professional degree
• Number of Employees: 501-1,000 employees