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Assistant/Associate/Full Professor - College of Engineering - Civil and Environmental Engineering - Intelligent Infrastructure - Boston

Northeastern University · Massachusetts

📍 Boston, MA (Main Campus)via workdayFirst listed here 2026-09-28
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About the Opportunity Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned experiential approach empowers our students, faculty, alumni, and partners to create impact far beyond the confines of discipline, degree, and campus. Our locations—in Arlington; Boston; Charlotte, North Carolina; London; Miami; New York City; Oakland; Portland, Maine; Seattle; Silicon Valley; Toronto; Vancouver; and the Massachusetts communities of Burlington and Nahant—are nodes in our growing global university system. Through this network, we expand opportunities for flexible, student-centered learning and collaborative, solutions-focused research. Northeastern’s comprehensive array of undergraduate and graduate programs— in a variety of on-campus and online formats—lead to degrees through the doctorate in nine colleges and schools. Among these, we offer more than 195 multi-discipline majors and degrees designed to prepare students for purposeful lives and careers. About CEE and COE at Northeastern University:  The Department of Civil and Environmental Engineering (CEE) at Northeastern University has a faculty of more than 40 members (several with joint appointments with other colleges) pursuing use-inspired research in structures, urban coastal systems, urban transportation and mobility, construction management, air quality, wind energy, water quality, environmental health, resilience, sustainability and climate change, life cycle assessment, green infrastructure, urban informatics, and robotics. CEE sits within Northeastern's  College of Engineering (COE) , a leader in experiential education and interdisciplinary research focused on innovating for global impact, anchored by Northeastern's signature cooperative education program and R1 research rating. The college enrolls more than 10,000 students pursuing BS, MS, and PhD degrees and includes more than 450 faculty. COE leads four university-wide research institutes while partnering in ten more and brings together researchers from a global network of campuses and partners. About the Opportunity: As part of a strategic initiative, coordinated across the university under the broad theme of Physical AI, Robotics & Autonomous Systems , the Department of Civil and Environmental Engineering Department at Northeastern University seeks faculty candidates for tenured or tenure-track appointments at the assistant, associate, or full professor ranks. The university-wide Physical AI, Robotics & Autonomous Systems theme brings together researchers working at the intersection of artificial intelligence, robotics, and the physical world to build systems that sense, reason, and act in real-world environments. The theme spans intelligent infrastructure and adaptive construction and manufacturing; embodied and wearable AI and human-robot collaboration; automated laboratories for chemistry, materials, and biomanufacturing; AI-enabled telepresence; and physical AI applications in health. Within this theme, the position focuses on Intelligent infrastructure, construction and manufacturing; adaptive robotics & digital twins. The position draws on cross-college collaboration among the College of Engineering, Khoury College of Computer Sciences, the College of Arts, Media and Design, and the College of Science. It is further strengthened by Northeastern's recently launched Physical AI Research (PAIR) Initiative, by the Institute for Experiential Robotics (IER), and by the Institute for Experiential AI (EAI). Appointments will be primarily or fully in the Department of Civil and Environmental Engineering (CEE) within Northeastern University’s College of Engineering, with opportunities for joint cross-college appointments with the College of Arts, Media and Design, the Khoury College of Computer Sciences, or the College of Science. The position will be based primarily on Northeastern University’s Boston campus. Candidates with interest in joint appointments with other departments or colleges should indicate their intent in their application materials in the cover letter. For this position we seek candidates who will leverage advances in AI, automation, digital twins, and sensing to transform construction and construction management; innovate in infrastructure systems adaptation, operations, control, and inspection; and advance human-robot collaboration. The term infrastructure systems refers to all aspects of the built environment (such as dams and reservoirs, buildings and bridges, transportation systems and water distribution networks, energy systems). Candidates working broadly in these fields are encouraged to apply, but example areas of interest include: Construction automation and construction management: AI-enabled construction management for planning, resource allocation, and on-site decision support; infrastructure robotic fabrication and assembly, automated inspection, and site-scale sensing and control; autonomy in complex and dynamic construction environments under uncertainty; AI-enabled digital twins for construction; human-robot interaction for construction and infrastructure focusing on safe and adaptive teaming between people and autonomous systems; human-in-the-loop control; multimodal and wearable sensing; transforming the design and construction methods that are required to effectively reuse structures and/or materials. Physical AI for infrastructure materials: Discovery and/or characterization of novel materials for construction and infrastructure maintenance; repurposing of materials to improve the sustainability and resilience of infrastructure systems; transforming the design and construction methods that are required to effectively use new materials. Autonomous mobility: Autonomous vehicle control and trajectory planning; mixed traffic with fleets of autonomous vehicles; AI-enabled planning, operations, and control of urban mobility systems f

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