Researcher Phd Student

3 weeks ago

Waterloo ON, Canada University of Waterloo Full time

Introduction

Computer Vision for Smart Structure Laboratory (CVISS) at the University of Waterloo, led by Dr. Chul Min Yeum (
//uwaterloo.Ca/civil-environmental-engineering/profile/cmyeum), invites applications for graduate studies ( Direct Ph.D ., Ph.D ., Postdoc ) in Civil and Environmental Engineering. CVISSlab (
//cviss.Net/) focuses on practical, application-driven research, utilizing advanced technologies to integrate intelligence into the physical built environment, aiming to enhance infrastructure safety and resilience.

Our lab is currently recruiting for four positions:

  • Robotics
  • Computer Vision
  • Nondestructive Testing
  • Flood Modelling

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Job Description 1 (Robotics)

The main task for the position will be to participate in the research projects on the development of mobile robotic sensing and analysis systems for infrastructure inspection and management and human-robot interaction for collaborative inspection. Students who have experience or knowledge in mobile robotics, computer vision, and augmented/virtual reality are recommended to apply for this position.

Qualification 1

Requirements

  • An undergraduate, MASc, or Ph.D. degree in Civil Engineering, Computer Science, Electrical Engineering, Mechatronics Engineering, Software Engineering, or System Engineering.
  • Familiarity with the Robot Operating System (ROS) 1 & 2.
  • Proven expertise in drone development, spanning flight control systems like PX4, autonomous mission design, and execution.
  • Knowledge in computer vision (e.G., Multiview geometry, SLAM), image recognition (e.G., DNN), and/or robotics (e.G., sensor fusion, mobile robotics).
  • Comprehensive knowledge of drone hardware, sensors, and communication protocols, including MAVLink.

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Job Description 2 (Computer Vision)

A key research objective for the position is designing, optimizing, and deploying 2D and 3D processing solutions that extract meaningful insights from visual data. Students will collaborate with a multidisciplinary team of engineers and researchers to deliver cutting-edge solutions that drive innovation in our field. Students who have experience or knowledge of deep learning and Multiview geometry are encouraged to apply for this position.

Qualification 2

Requirements

  • An undergraduate, MASc, or Ph.D. degree in Civil Engineering, Computer Science, Software Engineering, or System Engineering.
  • Strong machine learning development skills (TensorFlow, Keras, Pytorch, Lightning) and experience with OpenCV, C++, or/and C#.
  • Knowledge in image recognition (e.G., DNN) and computer vision (e.G., Multiview geometry, NERF, Gaussian Splatting)
  • Experience in processing and analyzing visual data from various sources, including images, videos, depth maps, and point clouds.

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Job Description 3 (Nondestructive Testing)

A primary research goal for this position is evaluating the quality and safety of various infrastructure (e.G., reinforced concrete or steel structures) utilizing Non-destructive Testing (NDT). Students will collaborate with a multidisciplinary team of engineers and researchers to deliver cutting-edge solutions that drive innovation in our field. Students who have experience or knowledge of NDT are encouraged to apply for this position.

Qualification 3

Requirements

  • An undergraduate, MASc, or Ph.D. degree in Civil Engineering, Mechanical Engineering, Electrical Engineering or equivalent.
  • Expertise in working with signal/imaging processing, including but not limited to AI/ML libraries.
  • Extensive experience in NDT methods including visual inspection, ultrasonic wave, and electromagnetic wave.
  • Excellent proficiency in software or tools, such as Python, Matlab, LabView, or similar.

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Job Description 4 (Graph Networks for Flood Modelling)

This position is to develop and apply for graph networks/ graph neural networks, for flood modeling and flood hazard assessment. The successful candidate will participate in research projects aimed at improving flood prediction, risk assessment, and decision-making tools in the context of climate resilience.

Qualification 4

Requirements

  • An undergraduate, M.Sc., or Ph.D. degree in Civil Engineering, Environmental Engineering, or other relevant fields.
  • Experience in graph networks/ graph neural networks and/or data-driven based approaches for flood modelling and prediction.
  • Proficiency in programming languages such as Python and familiarity with relevant libraries (e.G., PyTorch Geometric, TensorFlow, NetworkX).
  • Experience working with large and varied datasets, including hydrological, meteorological, and geographic information system (GIS) data, to build reliable flood hazard models.

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Preferred Qualifications

  • Proficiency in English, both spoken and written, to communicate daily.
  • Track record of publications in the areas of machine learning, computer vision, image processing, or structural health monitoring
  • Experience in operating and manipulating optical sensors (e.G., color, depth camera, lidar) and sensing hardware (e.G., DAQ)
  • Familiarity with Git for version control is preferred.

Duties and responsibilities

  • Coordinating research projects and delivering outputs.
  • Disseminating results through scientific publications and conference presentations.
  • Communicating and working with industries and stakeholders in government.
  • Participating in research proposal drafting and project deliverables.
  • Assisting in the organization of relevant workshops and demos.

Application

All qualified individuals are encouraged to apply for this position. The candidates should send a detailed CV to Dr. Yeum ( cmyeum@uwaterloo.ca ) with the email subject “Position Application”. Please do not apply for the position through the LinkedIn. Before applying to the position, please review the current research in our lab (
//cviss.Net or
//). Dr. Yeum may ask for additional information from the candidates.

Dr. Yeum will review the applications and contact candidates who meet the criteria to arrange interviews. If you do not hear from us, it means your application did not progress to the interview stage. Please do not send me a remainder. Selected candidates will have the opportunity to start the program in Winter 2025 (only for PR/Canadian), Spring 2025 or Fall 2025.

If you are passionate about applying the newest computer vision technologies to solve impactful civil engineering problems and want the opportunity to collaborate with leading industry partners, apply to our lab today

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