Visiting Scientific Specialist, Environmental Sciences

Visiting Scientific Specialist, Environmental Sciences Job Summary An entry-level position dedicated to developing novel research methods for exploring, visualizing, and leveraging the data available at the Illinois State Water Survey. Develop real-time integrations of hydrologic data into groundwater and integrated hydrologic models. Digitization of analog datasets to bring new scientific stories out of the "dark". 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. 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: Convolutional Neural Networks (CNNs) for pattern and trend analysis, Implementation of Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) for improving calibration optimization with modeled dataset, 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: Comparisons of 1950s drought groundwater level data against modern drought data, Use artificial intelligence to query the historical data to find overlooked trends, patterns, and processes, 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. Physical Demands and Working Conditions The work is sedentary and involves remaining in a stationary position for extended periods of time working at a computer, using a keyboard and mouse, and using repetitive hand motions. Minimum Qualifications Bachelor’s degree in hydrology, geology, civil engineering, or another similar technical field. Alternate degree fields will be considered depending on the nature and depth of the experience as it relates to this position. Experience writing programming scripts for data visualization and analysis, including course work. Experience with Git for version control, including course work. Familiarity with SQL for database queries.??? Wait: fix content.-->Sorry for previous confusion. The final JSON is as below. } #J-18808-Ljbffr Laseagrant