⛔ This position is no longer available.
University: University of Rhode Island
Country: United States
Deadline: Not specified
Fields: Mechanical Engineering, Civil Engineering, Ocean Engineering, Structural Health Monitoring, Data Science
Are you passionate about advancing the safety and resilience of critical infrastructure through cutting-edge research in structural health monitoring and smart sensing technologies? If you are eager to develop innovative solutions that combine experimental, numerical, and data-driven approaches, the University of Rhode Island offers an exceptional opportunity to pursue a fully funded PhD position in Mechanical or Civil Engineering starting Fall 2026.
About the University or Research Institute
The University of Rhode Island (URI) is a renowned public research university located in Kingston, Rhode Island, USA. As the state’s flagship university, URI is recognized for its commitment to research excellence, innovation, and fostering a collaborative academic environment. The College of Engineering at URI stands out for its interdisciplinary research, state-of-the-art facilities, and strong industry and governmental partnerships. URI’s picturesque campus, situated near the Atlantic coast, provides a vibrant and supportive community for graduate students, offering numerous resources for academic, professional, and personal growth.
Studying in the United States not only offers access to world-class education and research infrastructure but also provides exposure to a diverse and multicultural academic environment. Students at URI benefit from proximity to major metropolitan areas, such as Boston and New York City, and from the university’s active engagement in addressing real-world engineering challenges relevant to both local and global contexts.
Research Topic and Significance
This PhD position centers on advanced research in structural health monitoring, damage diagnosis, and prognosis. The focus is on developing and applying both physics-based and data-driven digital twin technologies for the monitoring and assessment of complex engineering systems. These research areas are critically important in today’s world, where the safety, reliability, and sustainability of infrastructure—bridges, buildings, coastal structures, and more—are paramount.
Structural health monitoring (SHM) is a rapidly growing field that leverages smart sensing, advanced data analytics, and artificial intelligence to detect damage, predict failures, and inform maintenance strategies. By integrating experimental, numerical, and field-based monitoring, this research aims to create interpretable and practical methods for long-term infrastructure management. The application of digital twins—virtual replicas of physical assets—represents a transformative approach for real-time monitoring and decision-making in engineering.
Project Details
The successful candidate will join a dynamic research group led by Dr. Vahid Jahangiri at the University of Rhode Island. The group’s work spans advanced monitoring and digital-twin approaches, focusing on interpretable and practical solutions for condition assessment and damage detection in civil and coastal infrastructure. Current projects involve smart sensing, hybrid physics-based and AI-enabled modeling, and data-driven analysis, with applications across multiple engineering domains.
The position is fully funded, offering either a Research Assistantship (RA) or Teaching Assistantship (TA), depending on availability. This support includes tuition coverage and a competitive stipend, providing an excellent foundation for academic and professional development.
Candidate Profile
Ideal candidates for this PhD position will have:
– A bachelor’s or master’s degree in mechanical engineering, civil engineering, ocean engineering, or a closely related field.
– Familiarity with system monitoring and system identification techniques.
– Programming experience in MATLAB, Python, or similar languages.
– Strong verbal and written communication skills.
– A keen interest in research that combines experimental, numerical, and data-driven approaches to engineering challenges.
– Motivation to work in a collaborative, interdisciplinary research environment.
Priority will be given to candidates currently in the United States who are able to begin immediately.
Application Process
Interested applicants should prepare the following materials:
– A full curriculum vitae (CV)
– Copies of unofficial transcripts
– A cover letter describing their research background and motivation for applying
These documents should be sent as specified in the official advertisement. For further details and to apply, please refer to the LinkedIn post by Dr. Vahid Jahangiri:
https://www.linkedin.com/posts/vahid-jahangiri-phd_shm-ugcPost-7447471998399602688-AkQq
Conclusion
This fully funded PhD position at the University of Rhode Island offers an exciting opportunity to contribute to the advancement of structural health monitoring and digital twin technologies. If you are driven to make a tangible impact on the safety and sustainability of our built environment, consider applying to join a leading research group in a supportive and resource-rich academic setting. Stay tuned for similar opportunities in engineering and related fields below this post.
Questions & Answers
Question: What are the main research areas for this PhD position?
The primary research areas include structural health monitoring, damage diagnosis and prognosis, structural dynamics, smart sensing, and the development of digital twins using both physics-based and data-driven approaches.
Question: What makes the University of Rhode Island a strong choice for graduate studies?
URI offers a collaborative research environment, modern facilities, and strong connections with industry and government. Its location in Rhode Island provides access to a vibrant academic community and proximity to major East Coast cities.
Question: What qualifications are required for applicants?
Applicants should hold a bachelor’s or master’s degree in mechanical engineering, civil engineering, ocean engineering, or a related field, with relevant skills in system monitoring, programming, and communication.
Question: How can I apply for this position?
Please refer to the official advertisement for application details. For more information and the application process, visit the LinkedIn post:
https://www.linkedin.com/posts/vahid-jahangiri-phd_shm-ugcPost-7447471998399602688-AkQq
Want to calculate your PhD admission chances? Try it here:
https://phdfinder.com/phd_admission_chance_calculator/
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