Assistant Professor (Spatial Statistics and GeoAI) (0084868)

Title: Assistant Professor (Spatial Statistics and GeoAI)
Position Number:
Hiring Unit: UHM College of Social Sciences Department of Geography and Environment
Location: Manoa Campus
Date Posted: 09/23/2026
Closing Date: Continuous; review of applications will begin 11/16/2026 and will continue until the position is filled. Applications received by 11/15/2026 will be given priority.
Salary Information: Commensurate with qualifications and experience
Monthly Type: 9 Month
Tenure Track: Tenure Track
Full Time/Part Time: Full Time
Temporary/Permanent: Permanent

Other Conditions:
The Department of Geography and Environment College of Social Sciences University of Hawaii at Manoa (UHM Honolulu Hawaii) invites applications for an Assistant Professor (F-3) in Spatial Statistics and Geospatial Artificial Intelligence (GeoAI). This is a 9-month full-time permanent tenure-track faculty appointment to begin August 1 2027 subject to position clearance and availability of funds.

We seek a scholar whose research advances spatial statistics statistical learning machine learning or artificial intelligence (AI) for understanding geographic processes and social and environmental challenges. Candidates should demonstrate a strong foundation in spatial analysis and the ability to connect methodological development with substantive applications. Relevant application areas include but are not limited to environmental change human-environment interactions climate variability natural hazards land-use and land-cover change population dynamics spatial inequality health geography and agricultural and ecological systems. This position will strengthen the Departments expertise in spatial statistics complementing its existing strengths in geographic information science (GIS) and remote sensing. Together these three areas support an integrated approach to geospatial research and education. More information about the Department of Geography and Environment is available athttps:// position will participate and contribute to the College of Social Sciences new SODA (Social Science Data Analytics) initiative through the development and teaching of two shared undergraduate courses open to students across the College (covering topics in data science statistical learning machine learning and artificial intelligence for the social sciences) alongside advanced graduate instruction in spatial statistics.

UHM is an R1 (Very High Research Activity Carnegie Classification) institution located on a beautiful arboretum campus. UHM is a land-grant sea-grant space-grant and sun-grant university with the core mission of generating preserving and disseminating knowledge for the greater good of the people of the state of Hawaii and the world beyond.

Duties and Responsibilities

• Teach undergraduate and graduate courses such as Spatial Statistics Spatial Statistical Modeling and the College of Social Sciences shared quantitative-methods sequence (covering topics in data science statistical learning machine learning and artificial intelligence for the social sciences) developed as part of the Colleges new SODA initiative;
• Supervise and mentor MA and PhD students and support undergraduate research;
• Develop an active research program and publish scholarly peer-reviewed research in areas of expertise;
• Seek extramural funding to support research and student training;
• Provide service to the Department College University profession and community;
• Other duties as assigned by the Department Chair.

• Ph.D. in Geography Geographic Information Science Statistics or a closely related field from a college or university of recognized standing or foreign equivalent. ABD applicants will be considered but all degree requirements must be completed and the Ph.D. conferred before the date of hire;
• Demonstrated expertise in spatial statistics or spatial statistical modeling and in data science machine learning or artificial intelligence applied to geospatial data;
• Ability to teach undergraduate and graduate courses in areas of expertise and to teach statistical machine learning and AI methods to social science students;
• Proficiency in scientific programming using languages such as Python and/or R;
• Ability to mentor and advise students in the applicants area of research;
• A record of research achievement commensurate with time in the field;
• Demonstrated ability to maintain professionalism in meeting and conferring with others.

• Research that connects spatial statistics and GeoAI with substantive social or environmental questions and complements the Departments strengths in GIS and remote sensing.
• Experience teaching quantitative or computational methods using applied exercises and reproducible workflows.
• Demonstrated ability to achieve interdisciplinary collaboration and secure extramural funding.

• Cover letter addressing the minimum and desirable qualifications;
• Curriculum vitae;
• Statement of research experience and interests;
• Statement of teaching experience and interests including preparation to contribute to the shared SODA courses and graduate spatial statistics instruction;
• Summaries of teaching evaluations if available;
• Representative publication(s) or working paper(s);
• Three (3) letters of recommendation;
• Official transcripts (copies are acceptable for application; official transcripts will be required upon
  hire).

The University of Hawaii is an Equal Opportunity Institution and is committed to a policy of nondiscrimination in employment including on the basis of veteran and disability status. For more information visit: is contingent on satisfying employment eligibility verification requirements of the Immigration Reform and Control Act of 1986; reference checks of previous employers; and for certain positions criminal history record checks.

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Accommodation Request: The University of Hawaii complies with the provisions of the Americans with Disabilities Act (ADA). Applicants requiring a reasonable accommodation for any part of the application and hiring process should contact the EEO coordinator directly. Determination on requests for reasonable accommodation will be made on a case-by-case basis. For further information please refer to the following link: Experience:

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