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- Cluster Hire in Smart Cities, AI and Related Strategic Areas
Description
The Herff College of Engineering (HCoE) at the University of Memphis is pleased to announce multiple tenure-track Assistant Professor positions as part of a strategic cluster hire focused on the interdisciplinary theme of Smart Cities, with complementary emphasis in Artificial Intelligence (AI), Advanced Manufacturing, Engineered Materials, and Sustainable Energy and Environmental Systems. This initiative is designed to foster cross-disciplinary collaboration and to catalyze transformative research at the intersection of AI, technology, data science, infrastructure, and sustainability.
We seek visionary and forward-thinking scholars whose work advances the digital, energy-efficient, and environmentally sustainable transformation of urban environments, production systems, and materials design.
Applicants with expertise in enabling technologies—including artificial intelligence (AI), machine learning, or automation—are encouraged to apply, especially where such tools enhance engineering solutions for complex urban and industrial systems.
This cluster hire aligns with one of the College’s core strategic priorities: to grow targeted research areas with strong potential for national impact, expanded external funding, and regional application. The new faculty will collaborate across disciplines and with existing faculty experts to contribute to a vibrant and inclusive research ecosystem that enhances the College’s national leadership in Smart Cities innovation and beyond.
The Smart Cities theme is at the forefront of national and global priorities for urban resilience, sustainability, and innovation. In support of this vision, special consideration will be given to candidates whose expertise falls within the following areas:
Smart Infrastructure & Urban Planning – urban-scale integration of cyber-physical systems and IoT; intelligent infrastructure and mobility systems; data-driven urban planning and digital twins; circular economy models and sustainable city design; green infrastructure and nature-based solutions; urban resilience and disaster risk management; computational and AI-assisted planning tools
Energy & Environment – renewable energy integration and smart grid optimization; electrification, energy storage, and hydrogen technologies; urban energy modeling and environmental sensing; water-energy nexus and resource-efficient urban ecosystems; data analytics and machine learning for energy forecasting
Advanced Manufacturing –metals, polymers, composites; robotics, automation, and cyber-physical production systems; sustainable, low-carbon, or circular manufacturing processes; smart supply chains and urban manufacturing integration; AI-supported process control and predictive maintenance; advanced manufacturing systems and automation including additive, hybrid and smart manufacturing
Engineered and Functional Materials – smart and sustainable infrastructure materials design and characterization; energy and sensing materials for resilient cities; circular and low-impact materials and manufacturing; integrated urban supply chains and localized production; computational methods and data-driven materials design
The Herff College of Engineering is committed to fostering interdisciplinary collaboration and providing the support necessary for faculty to succeed in advancing impactful, forward-thinking research.
Requirements
Qualifications:
Required:
Ph.D. in Mechanical Engineering, Materials Science, Civil and Environmental Engineering, Energy Systems, Urban Engineering, Electrical & Computer Engineering or a related discipline
Evidence of research excellence and potential for securing independent funding
Demonstrated commitment to teaching and mentoring at undergraduate and graduate levels
Strong interest in interdisciplinary research aligned with the theme of “Smart Cities”
Preferred:
Experience in one or more of the cluster focus areas
A track record of collaborative or cross-disciplinary work
Engagement with societal impact, public-private partnerships, or technology deployment.