Assistant Teaching Professor
$80,000–$85,000 year
On-siteWorcester, Massachusetts, United States
Job Summary
Teach undergraduate and graduate courses in construction automation, robotics, uncrewed aerial systems, sensing, digital twins, and data-driven infrastructure asset management. Develop new courses and laboratory modules providing direct student experience with robotic platforms, drones, and field data collection. Advise and mentor students in project-based curricula including Major Qualifying Projects and graduate capstones. Contribute to laboratory and field-testing facility design while building industry relationships to align instruction with current practice. Participate in departmental service, student recruiting, curriculum assessment, and ABET accreditation activities. This career-track appointment offers a clear path to Associate and Teaching Professor with central curricular leadership roles.
Required Qualifications
- An earned doctorate by the appointment start date in civil, architectural, construction, mechanical, or robotics engineering; computer science; or a closely related field.
- Demonstrated technical depth in at least two of the following, with the ability to teach in both: construction robotics and automation; UAS/drone operations and reality capture; sensing, instrumentation, and structural health monitoring; digital twins and BIM-integrated workflows; applied machine learning or computer vision for the built environment; data-driven infrastructure asset management and condition assessment.
- Clear anchoring in civil, architectural, or construction engineering practice.
- The successful candidate will be able to connect computational and robotic methods to real construction operations, structural behavior, or infrastructure management, not to treat the built environment solely as an application domain.
- Evidence of, or clear potential for, excellence in undergraduate and graduate teaching.
- Commitment to hands-on, project-based, and experiential instruction.
Desired Qualifications
- Prior university-level teaching experience, including course and laboratory development.
- Professional experience in the construction industry, with an infrastructure owner or agency, or in a construction technology firm.
- Experience deploying robotic, sensing, or autonomous systems in field conditions
- Working fluency with relevant tooling: Python and modern ML frameworks, ROS, photogrammetry and LiDAR processing, sensor networks and data acquisition, BIM and computational design platforms, or construction and asset management software.
- Experience building industry partnerships, sponsored student projects, or continuing education and workforce development programs.
- A record of mentoring students from a range of backgrounds and preparing them to work on diverse teams.
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