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Assistant Professor of Materials Engineering – Department of Manufacturing Systems Engineering and Management 26-08

Tenure-Track Faculty Position Announcement

Department: Manufacturing Systems Engineering and Management

Faculty Hire Number: #26-08

Rank: Assistant Professor

Effective Date of Appointment: August 19, 2026 (Subject to Budgetary Approval)

Anticipated Hiring Range: $105,000-$110,000 (Dependent upon qualifications)

CSUN’s Commitment to You:

CSUN is committed to achieving excellence through teaching, scholarship, learning, and inclusion. Our values include a respect for all people, building partnerships with the community, and the encouragement of innovation, experimentation, and creativity. CSUN strives to cultivate a community in which a diverse population can learn and work in an atmosphere of civility and respect. CSUN is especially interested in candidates who make contributions to equity and inclusion in the pursuit of excellence for all members of the university community.

As a Hispanic-serving Institution (HSI), inclusiveness and diversity are integral to CSUN’s commitment to excellence in teaching, research, and

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Job Summary:

With this posting, the Department of Civil and Environmental Engineering (CEE) at the University of Wisconsin-Madison (https://www.engr.wisc.edu/department/civil-environmental-engineering) is searching for an interdisciplinary tenure track faculty member at the intersection of civil and environmental engineering with artificial intelligence (AI) and machine learning (ML), as part of the RISE-AI Initiative (https://rise.wisc.edu/rise-ai/). We specifically seek candidates with expertise in the use of AI and/or ML to affect transformational advances in civil and environmental engineering. A successful candidate would conduct research and teach undergraduate and graduate courses in their engineering domain expertise, as well as on AI and/or ML and related topics. While we give the highest priority to the overall originality and promise of the candidate’s work, a successful candidate will have a deep knowledge of AI and/or ML in a domain relevant to some part of civil or environmental engineering applications. We particularly welcome

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