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University of Notre Dame


Postdoctoral Research Fellow in Sustainability and Data Science

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Recruitment began on September 25, 2025
and the job listing Expires on December 25, 2025
Notre Dame, IN Full-time
Apply Now

*Applications will be reviewed on a rolling basis starting on November 1, 2025

Description

The University of Notre Dame invites applications for a cohort of outstanding Postdoctoral Research Fellows with deep expertise in quantitative data analysis, data science, and artificial intelligence (AI). These fellows 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 fellows will contribute to a new research project that is creating a Pan-Amazon Evidence and Action Hub for socio-economic and ecological flourishing in Amazonia. 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 cohort will function 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 fellows 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.
  • Harmonize, curate, and provide customized datasets across multiple spatial and temporal resolutions tailored to specific research questions and stakeholder needs.
  • 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, Environmental Science, Sustainability Studies, or a related field with a strong quantitative focus. Applicants with an interdisciplinary degree are welcome.
  • Demonstrated proficiency in data management, data harmonization, and advanced data analysis techniques.
  • Strong programming skills in Python, R, and/or similar software.
  • Experience working with large and complex datasets, including geospatial and temporal data.
  • A strong publication record in data-driven sustainability research or closely related fields.
  • Excellent communication skills and an ability to work collaboratively with researchers from a wide range of disciplines.
  • Spanish language fluency or professional proficiency

Preferred Qualifications:

  • Experience working with socioeconomic data or other indicators of human wellbeing.
  • Experience working in multidisciplinary teams with researchers from diverse backgrounds.

Application Instructions

Applications will be reviewed on a rolling basis starting on November 1, 2025 and will continue until the positions are filled.

 

Interested applicants should submit the following materials at their earliest convenience.

  1. A cover letter that describes in detail how their research background and qualifications correspond to the position description outlined above.
  2. A detailed CV, including a list of conference presentations, publications, and research collaborations.
  3. A recent publication or dissertation chapter.
  4. Contact information for at least three references.
Apply Now

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  • 01 Occupation Description
  • 02 Employment Trends
  • 03 Top Employers
  • 04 Education Levels
  • 05 Annual Earnings
  • 06 Technical Skills
  • 07 Core Competencies
  • 08 Job Titles

Occupation Description

Employment Trends

The number of jobs in the career for the past two years, the current year, and projections for the next 10 years. Job counts include both employed and self-employed persons, and do not distinguish between full- and part-time jobs. Sources include Emsi industry data, staffing patterns, and OES data.

Top Employers

These companies are currently hiring for .

    Education Levels

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    Technical Skills

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      Core Competencies

      The skills for the career. The "importance" is how relevant the ability is to the occupation: scale of 1-5. The "level" is the proficiency required by the occupation: scale of 0-100. Results are sorted by importance first, then level.

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