Job Description

How to Apply

The position will be filled at the assistant professor (tenure-track) or associate professor (tenured) level.

Applications should include (1) a cover letter; (2) CV; (3) a concise personal statement describing your vision and plans for research, teaching and societal engagement; (4) a one-page statement that showcases a demonstrated commitment to diversity efforts, and (5) a list of three names of academic references with contact information.

To apply, submit application materials in Interfolio, via this link: http://apply.interfolio.com/156521

Review of applications will begin on November 15, 2024 and continue until the position is filled. SEAS hopes to appoint a faculty member to this position to begin Fall 2025.

Job Summary

The School for Environment and Sustainability (SEAS) at the University of Michigan invites applicants for a full-time, nine-month, tenure-track Assistant/Associate Professor in Artificial Intelligence, Biodiversity, and Society beginning Fall 2025. The position is part of a two-position cluster hire in Artificial Intelligence for Sustainability using cutting edge technologies to address questions at the intersection of society and the environment. The second position is in AI and Sustainable Systems: http://apply.interfolio.com/156525

We seek a candidate whose teaching and research interests focus on understanding the drivers of change in biodiversity and the implications of those changes for ecosystems and societies, using cutting edge AI techniques to advance their research. Importantly, we are seeking candidates who have an interest in using their research to help solve real-world sustainability challenges.

Areas of interest include, but are not limited to, the human influence on biodiversity patterns and processes, biodiversity and ecosystem services, and reciprocal interactions between biodiversity and society. Preference will be given to a candidate that demonstrates the ability to (i) use or develop AI methodologies, (ii) innovatively handle big and heterogeneous datasets to decipher complex patterns, and (iii) address the ethics of AI in their research and teaching.

Mission Statement

SEAS's mission is to contribute to the protection of the Earth's resources and the achievement of a sustainable and just society. The School contributes new scientific knowledge, visionary leadership, and trained professionals toward that end. The faculty of the School is diverse, with natural scientists, social scientists, engineers, and designers working collaboratively in an integrative setting. A professional school set within a major research university, SEAS provides a model of interdisciplinary and applied research and a focal point of research, teaching and societal engagement on sustainability. The School focuses on key cross-cutting sustainability themes, including climate and energy; water; food, land use, and agriculture; conservation and restoration; and cities, the built environment, and mobility. There are many opportunities for research collaborations through institutes such as the Michigan Institute for Data & AI in Society and the Institute for Global Change Biology.

The School offers a Ph.D. as well as both research and professional M.S. degrees in seven specializations: ecosystem science and management; geospatial data science; sustainable systems; environmental policy and planning; behavior, education and communication; environmental justice; and sustainability and development. The School also offers a Master's
degree in Landscape Architecture (M.L.A.). The student body includes over 500 M.S./M.L.A. and 60 doctoral students. SEAS also co-manages an undergraduate Program in the Environment and participates in dual master degree programs with the Schools of Architecture and Urban Planning, Business, Engineering, Law, Public Health, and Public Policy. Additional information about the School can be found at https://seas.umich.edu/

At SEAS we are committed to creating and maintaining an inclusive and equitable environment that respects diverse experiences, promotes generous listening and communications, and discourages and restoratively responds to acts of discrimination, harassment, or injustice. Our commitment to diversity, equity and inclusion is deeply rooted in our values for a sustainable and just society.

Why Work at Michigan?

In addition to a career filled with purpose and opportunity, The University of Michigan offers a competitive salary and comprehensive benefits package to help you stay well, protect yourself and your family and plan for a secure future. Benefits include:

Required Qualifications*

Candidates must have a Ph.D. in geography, ecology, computer science, engineering, environmental science, or other fields bringing AI analytical approaches to understanding the relationships between biodiversity and society. Candidates must have a strong record of scholarly publication, evidence of teaching potential in a multidisciplinary setting, as well as activities demonstrating a potential for and/or trajectory towards national and international recognition.

Priority will be given to applicants whose research programs complement or align with one or more current research strengths in SEAS (e.g., environmental justice, sustainable systems, ecosystem science and management).
 

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Additional Information

Salary and professor level will be determined based on experience.
 

Application Deadline

Job openings are posted for a minimum of seven calendar days. This job may be removed from posting boards and filled any time after the minimum posting period has ended.

Applications will be reviewed as received throughout the posting period and continue until the position is filled.
 

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.

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