Description
Applications are currently being accepted for a fully funded PhD position within the SENSORS Research Group at the University of Massachusetts Lowell. This opportunity is supported through a prestigious NSF-funded project that sits at the intersection of computer vision, robotics, sensing technologies, and structural dynamics. The University of Massachusetts Lowell is a nationally recognized public research institution committed to innovation and academic excellence. The SENSORS Research Group is known for its cutting-edge work in structural health monitoring, smart sensing, and UAV systems.
Responsibilities
The selected candidate will contribute to the development and experimental validation of UAV-based stereo vision systems for high-precision 3D measurement and real-time structural health monitoring. The role offers a unique blend of theoretical algorithm design and field-based deployment, targeting large-scale infrastructure assessment.
Benefits & Opportunities
- Up to five years of full funding (includes tuition and stipend)
- Access to cutting-edge laboratories, UAV platforms, and hands-on field deployment
- Opportunities to:
- Publish in peer-reviewed venues
- Mentor undergraduate students
- Engage in outreach and leadership development
Qualification
Minimum Qualifications
- An M.S. degree (by the start date) in Mechanical Engineering, Electrical Engineering, Mechatronics, Computer Science, or a closely related discipline is required. Note: Applicants holding only a B.S. degree will not be considered.
- A strong background in traditional computer vision techniques is essential, including:
- Stereophotogrammetry
- Digital image correlation
- Optical motion magnification
- Multi-view geometry and camera calibration
- Proficiency in programming languages such as Python, C++, MATLAB, OpenCV, or ROS.
- Practical experience with:
- Sensor fusion (e.g., GPS + IMU + stereo vision)
- Unmanned Aerial Vehicles (UAVs)
- Experimental sensing systems
- Effective communication and collaboration skills.
- Demonstrated interest in STEM outreach or curriculum development is desirable.
Note: This position does not involve the use of machine learning or AI-based vision systems. Experience with deep-learning object detection is not required or prioritized.
Application Instructions
Applications must be submitted by email to Dr. Alessandro Sabato at:
📧 Alessandro_Sabato[at]uml.edu
Subject Line: Ph.D. UAV-based stereovision
Required materials:
- A one-page statement of research interests
- A detailed CV (highlighting relevant projects and publications)
- Unofficial academic transcripts
- Contact information for 2–3 references
Applications will be reviewed on a rolling basis until the position is filled. Both U.S. and international candidates will be considered. Due to a high volume of applications, only shortlisted candidates will be contacted for interviews.
