Visiting Scientific Specialist, Environmental Sciences

University of Illinois Urbana-Champaign; Urbana (IL); On-site; USD 80,000 - 120,000; Full time

Job summary

University of Illinois Urbana-Champaign is seeking a researcher to support research development in hydrogeology and data science. The role involves building and improving data pipelines from databases to models and visualizations, enabling participatory modeling with community stakeholders.

The position emphasizes developing online dashboards, backend APIs, and AI-assisted tools, with opportunities to present findings at conferences and contribute to teaching materials for environmental

Responsibilities

• Research Development – 75%: streamline data pipeline from databases to hydrogeologic models and visualizations for participatory modeling with community stakeholders.
• Research Dissemination and Teaching – 20%: present newly developed tools and visualizations at professional conferences and invited seminars; develop teaching materials for researchers.
• Other – 5%: perform other duties as needed to further the mission of the Survey, PRI, and the University.

Job description

Duties & Responsibilities

• Research Development - 75% Work with ISWS databases to streamline data pipeline from database to hydrogeologic models and visualizations for participatory modeling with community stakeholders. o Pipeline could include: Amazon Web Services, Parquet files, Delta and DeltaAI, and LLMFlux. Establish and build working relationship with the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign. Develop software and services to share and explore ISWS, ISGS, and other PRI datasets. For example, contribute to the development of online dashboards, and backend APIs for allowing researchers to view more of their data in one common location. Develop parallelization schema for data pipeline from database to AWS buckets and Data Lakes. Research the integration with artificial intelligence tools with PRI datasets, including: o Convolutional Neural Networks (CNNs) for pattern and trend analysis o Implementation of Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) for improving calibration optimization with modeled datasets o Employing large language models (LLMs) to explore more than one hundred years of analog data at PRI Develop software and tools for digitizing “dark data” – i.e., handwritten data that is not easily incorporated into digital automated workflows. Investigations could include: o Comparisons of 1950s drought groundwater level data against modern drought data. o Use artificial intelligence to query the historical data to find overlooked trends, patterns, and processes. o Meta-analysis of AI-identified trends against human observations to determine how LLMs are missing (or not) important subject matter expertise. Integration of data pipeline into groundwater modeling infrastructure—i.e., MODFLOW6 and FloPy—towards building real-time model simulations.
• Research Dissemination and Teaching – 20% Present newly developed tools and visualizations at professional conferences, symposiums, and invited seminars. Poster and oral presentations, as well as tabling information booths at public outreach events (e.g., State Fair). Developing teaching materials for teaching environmental scientists, geologists, hydrologists, and ecologists to leverage machine learning and artificial intelligence tools for their research Serving as an invited lecturer for both internal and external courses
• Other – 5% Perform other duties as needed to further the mission and goals of the Survey, PRI, and the University of Illinois. Keep abreast of developments in this discipline