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Geospatial Ai Jobs in Indiana (NOW HIRING)

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Geospatial Ai information

How do geospatial AI professionals typically collaborate with other teams to deliver actionable insights?

Geospatial AI professionals often work closely with data scientists, GIS analysts, software engineers, and domain experts to develop, validate, and deploy spatial models. Collaboration usually involves integrating spatial data with machine learning algorithms, ensuring data quality, and tailoring outputs to meet the needs of end users such as urban planners or environmental scientists. Regular meetings, shared project management tools, and cross-functional workshops are common, fostering a collaborative environment that accelerates problem-solving and innovation.

What are the key skills and qualifications needed to thrive as a geospatial AI specialist, and why are they important?

To thrive as a Geospatial AI Specialist, you need a strong background in geospatial analysis, machine learning, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Familiarity with GIS platforms (such as ArcGIS or QGIS), remote sensing software, and AI/ML frameworks like TensorFlow or PyTorch is essential. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting complex data and collaborating with multidisciplinary teams. These competencies are crucial to develop innovative geospatial solutions that drive decision-making across sectors like urban planning, environmental monitoring, and logistics.

What is the difference between Geospatial Ai vs GIS Analyst?

AspectGeospatial AiGIS Analyst
Required CredentialsDegree in GIS, Computer Science, or related; experience with AI/ML toolsDegree in Geography, GIS, or related; proficiency in GIS software
Work EnvironmentTech-focused, data science teams, field data collectionOffice-based, mapping, spatial data analysis
Industry UsageTech companies, AI-driven mapping, autonomous systemsGovernment, urban planning, environmental management
Search & Comparison IntentFocus on AI applications in geospatial dataFocus on traditional spatial data analysis

Geospatial Ai combines artificial intelligence techniques with geospatial data analysis, often involving machine learning and data modeling. GIS Analysts primarily focus on mapping, spatial data management, and traditional geographic information systems. While both roles work with spatial data, Geospatial Ai emphasizes AI-driven insights, whereas GIS Analysts concentrate on spatial data visualization and analysis using GIS software.

What are popular job titles related to Geospatial Ai jobs in Indiana?

For Geospatial Ai jobs in Indiana, the most frequently searched job titles are:

What cities in Indiana are hiring for Geospatial Ai jobs?

Cities in Indiana with the most Geospatial Ai job openings:

Infographic showing various Geospatial Ai job openings in Indiana as of August 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 79% In-person, 3% Hybrid, and 18% Remote job distribution.

Postdoctoral Research Fellow - Midwest Regional Energy Symbiosis

University of Notre Dame

Notre Dame, IN • On-site

$48K - $65K/yr

Full-time

Re-posted 9 days ago


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Company rating: 7.4 out of 10

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Job description

Company Description

The University of Notre Dame is more than a workplace! We are a vibrant, mission-driven community where every employee is valued and supported. Rooted in a tradition of excellence and inspired by our Catholic character, Notre Dame is committed to fostering an environment of care that nurtures the whole person—mind, body, and spirit. Here, you will find a deep sense of belonging, a culture that prioritizes well-being, and the opportunity to grow your career while being a force for good in the world. Whether contributing to world-class research, shaping the student experience, or supporting the University’s mission in other ways, you will be part of a dedicated team working to make a meaningful impact on campus and beyond. At Notre Dame, your work matters, and so do you!

Job Description

This Postdoctoral Fellow position is being managed through a separate application system. We are sharing here to increase visibility and accessibility. Applications will be reviewed on a rolling basis starting on September 1, 2026, and will continue until the position is filled. Apply here if you are interested.

The University of Notre Dame invites applications for a Postdoctoral Research Fellow to join a collaborative, interdisciplinary team of researchers from Notre Dame, Indiana University, Purdue University, and the University of Wisconsin to develop and pilot an AI-enabled material flow and industrial symbiosis framework that connects energy, water, and resource loops. This innovative research engages the Midwest's strong presence in manufacturing, agricultural landscapes, construction activity, and freshwater resources as a living regional laboratory to develop transferable methods for mapping, modeling, and evaluating industrial symbiosis opportunities across interconnected energy, water, material, agricultural, industrial, and construction systems. The postdoctoral fellow will serve as the central analytical and coordination lead for the project, working under the technical guidance of the PI and co-investigators.

The postdoctoral fellow will contribute to key project outcomes, including, but not limited to:

  • Developing an innovative industrial symbiosis framework that outlines short-term feasible and long-term transformative cross-sector exchanges.
  • Creating a transparent AI-enabled and replicable methodology that can be adapted to other Midwestern and U.S. regions to support energy-water-resource engineering and circular economy research. 
  • Coordinating meetings and work with faculty teams and other research assistants. 
  • Lead the co-authorship of interdisciplinary, peer-reviewed publications in high impact journals and develop the foundation for future grant proposals.

The postdoctoral fellow will assume the following key responsibilities:

  • Compiling, managing, and integrating geospatial and infrastructure datasets related to industrial facilities, manufacturing processes, water and wastewater systems, solid waste streams, agricultural production, energy systems, construction-related material demand, and secondary resource flows.
  • Developing regional material flow inventories that identify major sources, sinks, transformation points, and potential exchange pathways. 
  • Conducting industrial symbiosis screening to identify feasible cross-sector resource exchanges. 
  • Supporting the development of transparent AI-enabled assessment methods.
  • Conducting simplified material flow analysis, life-cycle assessment, and techno-economic screening to evaluate selected symbiosis pathways.
  • Preparing technical briefs, maps, diagrams, scenario portfolios, and visualizations to support team coordination and communication with public and private sector partners.
  • Producing first drafts of scholarly manuscripts and contributing technical content, preliminary results, figures, and supporting analyses for follow-on grant proposals.

This search is conducted with leadership from Notre Dame’s Just Transformations to Sustainability Initiative, a University-wide effort to build a sustainable future where people and nature flourish together. The Initiative supports an interdisciplinary cohort of postdoctoral scholars dedicated to advancing sustainability research grounded in the principles of integral ecology and integral human development.

This is a full-time position available with an initial appointment of one-year, renewable for an additional year on the basis of satisfactory performance and availability of funding.

Qualifications
  • Ph.D. (in hand by the starting date) in industrial ecology, environmental engineering, civil and environmental engineering, systems engineering, sustainable manufacturing, urban systems, architecture/engineering, environmental science, geography, data science, or a closely related field.
  • Demonstrated research experience in one or more of the following areas: material flow analysis, life-cycle assessment, techno-economic analysis, industrial symbiosis, circular economy, resource recovery, waste management, water-energy-food systems, sustainable manufacturing, or low-carbon construction/material systems.
  • Strong quantitative and data-integration skills, including experience working with geospatial data, infrastructure datasets, environmental inventories, or regional-scale resource-flow data.
  • Expertise with LCA/MFA tools, databases, or methods; experience with software such as SimaPro, openLCA, Brightway, Python, R, GIS platforms, or related analytical tools is desirable.
  • Experience with AI, machine learning, optimization, spatial analysis, scenario modeling, or decision-support methods is strongly preferred, especially when applied in transparent, interpretable, or policy-relevant contexts.
  • Ability to synthesize complex multi-sector information into clear analytical outputs, including maps, figures, diagrams, tables, technical memos, and scholarly manuscripts.
  • Strong writing, communication, and coordination skills, with the ability to work across a multi-institutional and interdisciplinary research team.
  • Interest in regional sustainability, circular resource engineering, industrial ecology, and applied research that supports energy-water-resource loop closure.

Additional Information

The University of Notre Dame seeks to attract, develop, and retain the highest quality faculty, staff and administration. The University is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, national or ethnic origin, sex, disability, veteran status, genetic information, or age in employment. Moreover, Notre Dame prohibits discrimination against veterans or disabled qualified individuals, and complies with 41 CFR 60-741.5(a) and 41 CFR 60-300.5(a). We strongly encourage applications from candidates attracted to a university with a Catholic identity.


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