PhD in UAV Stereo Vision at UMass Lowell (Fully Funded)

University of Massachusetts Lowell

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Vacancy

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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:

1. Publish in peer-reviewed venues
2. Mentor undergraduate students
3. 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:

1. Stereophotogrammetry
2. Digital image correlation
3. Optical motion magnification
4. Multi-view geometry and camera calibration 

• Proficiency in programming languages such as Python, C++, MATLAB, OpenCV, or ROS.
• Practical experience with: 

1. Sensor fusion (e.g., GPS + IMU + stereo vision)
2. Unmanned Aerial Vehicles (UAVs)
3. 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.