Assistant Professor - Urban Analytics

Job Description

The Department of Urban Planning and Community Development (UPCD) in the School for the Environment at the University of Massachusetts Boston (UMB) invites applications for a full-time, tenure-track Assistant Professor position in Urban Analytics and Artificial Intelligence (AI) beginning September 1, 2027.

We seek scholars whose research and teaching integrate urban planning, computational methods, and artificial intelligence to examine complex challenges facing communities, cities, and regions. The successful candidate will contribute to planning scholarship and practice through community engaged and innovative applications of urban analytics and AI that support more equitable, inclusive, and sustainable communities, cities, and regions.

About UMass Boston: UMass Boston is an urban public research university with a teaching soul, whose impact is both local and global. We are the third most diverse university in the country - more than 60% of our undergraduate students come from minoritized communities and groups and more than half of our students are the first in their families to attend a college or university. Thus, our students come to us from richly diverse life experiences and backgrounds; they bring to our classrooms and research settings the robust range of perspectives growing out of the socio-cultural, economic, and historical contexts in which they have lived, along with the challenges they encounter, engage, and strive to overcome. We invite applications from candidates who engage the diverse life experiences of our student body, who appreciate that students bring their holistic selves into the academic setting, and who recognize and articulate how their own life experiences and backgrounds have shaped their journeys, practices, and commitments as researchers, scholars, and educators.

About the School for the Environment (SFE): SFE is an interdisciplinary hub at UMass Boston that tackles the diverse challenges of the natural, built, and social environments through teaching, research, and outreach. SFE engages in innovative, equity-driven approaches that address environmental and societal problems, focusing on the health of communities and ecosystems in the Greater Boston area and beyond. SFE offers undergraduate, master’s, and PhD programs, with faculty expertise spanning environmental science, environmental studies, marine science, and technology. At SFE, faculty and students collaborate to pursue transdisciplinary research and solutions, fostering partnerships with communities, organizations, and government agencies.

About the Department of Urban Planning and Community Development (UPCD): UPCD is a mission-driven program grounded in the pursuit of the just city and region, with a strong emphasis on equity, community development, and applied planning practice. The department has experienced steady growth in enrollment across its BA, Minor, and MS programs in recent years, reflecting increasing student demand for planning education that integrates analytical, policy, and community-engaged approaches.

This position represents a strategic investment in the future of planning education. As AI-enabled tools and computational approaches increasingly shape planning research and professional practice, this hire will play an important role in equipping students with advanced analytical, spatial, and computational skills, strengthening the department’s urban analytics and AI curriculum, supporting interdisciplinary collaboration across the university, and preparing graduates for a rapidly evolving planning profession shaped by advances in urban analytics and artificial intelligence.

The successful candidate will also have opportunities to collaborate with campus initiatives such as the Paul English Applied AI Institute, the Urban Harbors Institute, the Sustainable Solutions Lab, and other centers across the university, and contribute to interdisciplinary teaching and research across the university.

Position Overview

We seek candidates with expertise in Urban Analytics, broadly defined as the application of computational, statistical, and spatial methods to urban systems and planning challenges. Candidates should demonstrate the ability to bridge technical methods and planning practice, with a focus on addressing inequities and sustainability challenges in communities, cities and regions.

Substantive areas of interest include, but are not limited to:

• Climate, Public, and Municipal Finance (e.g., budget modeling, infrastructure finance, fiscal analytics)
• Transportation and Mobility Systems (e.g., accessibility modeling, intelligent transportation systems, equity in mobility and access)
• Environmental Planning and Urban Resilience (e.g., climate modeling, environmental justice analytics, risk assessment)
• Land Use, Zoning, and Urban Development (e.g., zoning and entitlement analysis, land-use change, development patterns, spatial modeling, growth management)

We are particularly interested in candidates whose work critically engages how data and AI can both reproduce and mitigate structural inequities in urban systems.

The successful candidate will be expected to develop and sustain an independent, externally funded research program in urban analytics or a related field; publish in high-impact, peer-reviewed journals; and engage in collaborative, interdisciplinary research across the School for the Environment and the broader university, with a focus on advancing equity, and justice. The candidate will teach core and elective courses in the BA and MS programs, including urban analytics, GIS and spatial analysis, and AI applications in urban systems. In addition, the candidate will mentor undergraduate and graduate students through advising, research supervision, and career development. Service responsibilities include active participation in departmental, college, and university governance, engagement with community partners and public and nonprofit sectors, and contributions to UPCD’s mission of community-engaged and practice-oriented planning education.

Qualifications

• A Ph.D. degree in Urban Planning or a closely related field by the start date. For candidates whose Ph.D. is outside of Urban Planning, a master’s degree in Urban Planning from a PAB-accredited program is preferred.
• Evidence of scholarly research and publication potential in urban planning, including demonstrated engagement with computational modeling, AI, and data visualization, alongside other appropriate methodological approaches.
• Demonstrated ability or potential to teach in areas related to urban analytics and computational methods integrating AI.
• Evidence of or potential for external research funding

Application instructions:

Interested individuals can initiate the application process by visiting the UMB’s Career Portal at

After completing the University’s basic employment application, candidates can upload the following documents:

• Cover letter (2 page maximum)
• Curriculum Vitae
• Research Statement
• Teaching Statement
• Complete contact information of three academic references

Application Deadline

Materials should be submitted via the UMB Employment Portal before October 18, 2026 , for maximum consideration by the UPCD Search Committee. For more information: Contact Sowmya Balachandran, Search Committee Chair, Department of Urban Planning and Community Development, School for the Environment, The University of Massachusetts Boston, at View email address on us.fitly.work.

UMass Boston expects to pay within an approximate range between $80,000 and $98,003 for this position.

The specific pay for this position will be determined by the University based on the consideration of all relevant factors when and if it decides to extend an offer of employment.

UMass Boston is committed to the full inclusion of all qualified individuals. As part of this commitment, we will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact View email address on us.fitly.work or View phone number on us.fitly.work.