Job Description

The University of Notre Dame invites applications for a Postdoctoral Research Fellow with deep expertise in quantitative data analysis, data science, and artificial intelligence (AI). This fellow will join a dynamic, interdisciplinary team working at the intersection of data innovation and sustainability science, aligned with the values and principles of integral ecology.

The research fellow will contribute to a new research project that is creating a Pan-Amazon Evidence and Action Hub for socio-economic and ecological flourishing. The hub will systematically synthesize and harmonize remote sensing, survey, census, and citizen science data to support analyses of issues for action in partnership with local communities and Indigenous Peoples in the Amazon region. Fellows will integrate and harmonize fragmented data from diverse sources into a coherent, usable form to support novel analyses that advance key sustainability goals. The work of the Hub will generate findings to support the design and adoption of interventions that respond to changing needs of the region and its people around climate change, energy, mining, soil and water contamination, food production and livelihoods.

The postdoctoral fellow will join a cohort that functions as a central research skills hub, supporting and elevating the sustainability-related research efforts of faculty and students across Notre Dame. The fellows will help advance impactful, solution-oriented sustainability research that engages ecological, social, economic, and ethical dimensions in an integrated manner.

The postdoctoral fellow will assume the following key responsibilities:

• Collaborate with faculty to design, implement, and support sustainability-related research projects requiring advanced data analytics.
• Develop and maintain a centralized platform for the Pan-Amazon Evidence and Action Hub that hosts diverse and harmonized sustainability-related datasets, including environmental, socioeconomic, cultural, and geospatial data.
• Design and implement reproducible pipelines that ingest, clean, and harmonize fragmented data from remote sensing, survey, census, administrative, and citizen science sources into coherent, analysis-ready datasets with documented lineage and quality metrics.
• Build tools and interfaces (APIs, catalogs, dashboards, or reproducible workflows) that make Hub data discoverable and usable by faculty, students, and partner organizations with varying technical capacity.
• Explore applications of AI methods, including large language models and natural language processing, for extracting structured information from unstructured sources(e.g. reports, policy documents, gray literature, or citizen science observations),
• Apply advanced statistical, machine learning, and AI techniques to analyze complex datasets and uncover actionable insights.
• Co-author and support high-impact, interdisciplinary research publications in leading sustainability and environmental science journals.
• Engage in collaborative grant writing and proposal development to sustain and expand the cohort’s research initiatives.

This search is conducted with leadership from Notre Dame’s Just Transformations to Sustainability Initiative and Data, AI, and Computing Initiative, both significant investments from the Provost’s Office. The Just Transformations to Sustainability Initiative is Notre Dame’s University-wide effort to build a sustainable future where people and nature flourish together. The Data, AI, and Computing Initiative’s core aim is to advance purposeful data, AI, and computing — excelling in foundational research while catalyzing interdisciplinary collaboration and real-world translation to address pressing societal challenges.

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

Required Qualifcations:

• Ph.D. (in hand by the starting date) in Data Science, Computer Science, Statistics, Geography, Environmental Science, or a related field with a strong computational focus. Applicants with interdisciplinary degrees are welcome.
• Strong data engineering skills in Python and/or R, preferably in building reusable data pipelines rather than one-off analysis scripts.
• Demonstrated experience harmonizing heterogeneous data sources: reconciling inconsistent schemas, units, geographies, and vintages across datasets such as remote sensing products, surveys, censuses, and administrative records, and documenting those decisions in a reproducible way.
• Expertise in geospatial data, including working across raster and vector formats, coordinate reference systems, and spatial aggregation or interpolation across mismatched administrative and ecological units.
• An interest or experience in using machine learning or AI tools with environmental or socioeconomic data
• Excellent communication skills and the ability to translate technical infrastructure decisions for collaborators from a wide range of disciplines.

Application Instructions

Interested candidates must submit a CV, cover letter, and a recent publication or dissertation chapter. Candidates should be prepared to share references upon request.

Equal Employment Opportunity Statement

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.

Background Check

This appointment is contingent upon the successful completion of a background check. Applicants will be asked to identify all felony convictions and/or pending felony charges. Felony convictions do not automatically bar an individual from employment. Each case will be examined separately to determine the appropriateness of employment in the particular position. Failure to be forthcoming or dishonesty with respect to felony disclosures can result in the disqualification of a candidate. The full procedure can be viewed at https://facultyhandbook.nd.edu/?id=link-73597