Tenure-Track Professor of Architecture and AI (Open Rank)

Summary

The University of Michigan Taubman College of Architecture and Urban Planning seeks a experimental practitioner and scholar at any rank (assistant, associate, or full professor) with a sharp analytical mind to join our faculty at the intersection of artificial intelligence (AI), digital studies, and the spatial disciplines of architecture, design, and urbanism.

We seek a colleague who will help us reimagine education and practice in architecture and / or urban design and technology in relation to emerging AI technologies.

You are an academic who is ready to engage with the complex and urgent questions that these fields face today. You will explore the accelerating influence of AI on the built environment, focusing on both applied and speculative approaches that challenge the boundaries of current disciplinary practices.

You will contribute to a body of work that is both intellectually challenging and innovative, providing a crucial framework for understanding AI's role in the future of our cities and built environments.

The teaching for this position will include courses in the core and advanced curricula of the architecture programs. We specifically seek applicants qualified to teach within the design studio sequence.

Faculty may also teach new electives that contribute to overall program goals. The standard teaching load at Taubman College is four courses per year.

Teaching will occur in person in Ann Arbor.

Required Qualifications*

The successful candidate's advanced degrees and scholarship might include, but not be limited to, any of the following :

• AI-driven architectural design including generative design, machine learning, multi-agent systems, and algorithmic techniques for spatial planning, volumetric design, and environmental performance design and modeling.
• AI-driven urban design and planning (smart cities, optimization of urban infrastructure, modeling and simulation, resource allocation, etc), predictive urban analytics (datasets analysis, modeling), generative design, digital twinning, simulated environment / scenario building, immersive space design, enhanced engagement processes.
• Cultural and social Impact studies (digital inequity and access), material intelligence (climate change intersection), mapping and spatial data visualization (systems mapping), digital humanities and spatial history / engaging with the theories of space and AI - addressing philosophical and theoretical questions.
• Critical AI studies, algorithmic visualization, ethics of machine learning, algorithmic governance and policy studies, the future of work, systems simulations, critical software, political implications of machine learning in societies and ecosystems, speculative futuring

Demonstrated experience in, or demonstrated potential for, excellence in design studio teaching and mentoring undergraduate and graduate students.

Demonstrated experience in, or demonstrated potential to, conduct funded research in the area of artificial intelligence (AI) and its impact(s) on the spatial disciplines of architecture, design, and urbanism