⛔ This position is no longer available.
University: University of Miami
Country: United States
Deadline: Not specified
Fields: Civil Engineering, Structural Engineering, Artificial Intelligence, Machine Learning, Smart Infrastructure
Are you passionate about revolutionizing civil infrastructure with artificial intelligence and eager to contribute to the next generation of smart cities? If you aim to build a career at the intersection of civil engineering and advanced computational methods, the University of Miami offers a unique, fully funded PhD/Postdoc position that could be your next academic step.
About the University or Research Institute
The University of Miami (UM) is a prestigious private research university located in the vibrant city of Miami, Florida. Consistently ranked among the top universities in the United States, UM is currently placed at number 64 in the US News 2026 rankings. The university is renowned for its commitment to academic excellence, cutting-edge research, and fostering a diverse and inclusive community. Situated in one of the most dynamic urban centers in the country, UM provides its scholars with unparalleled access to industry partnerships, a thriving multicultural environment, and a climate that encourages year-round innovation and collaboration. The Department of Civil & Architectural Engineering, housed within the School of Architecture, is recognized for its interdisciplinary research and engagement with global challenges in infrastructure and the built environment.
Research Topic and Significance
The available PhD/Postdoc position focuses on developing and applying large language models (LLMs) and AI agents to tackle pressing challenges in civil structures and infrastructure systems. With the rapid advancement of artificial intelligence, integrating machine learning and digital twin technologies into civil engineering is transforming how cities are designed, monitored, and maintained. Key research areas include leveraging LLMs and vision-language models (VLMs) for structural analysis, implementing uncertainty quantification and optimization through surrogate modeling, and enabling smart cities via digital twin frameworks.
This research holds significant promise for enhancing the safety, reliability, and sustainability of infrastructure systems. The integration of AI-driven tools into civil engineering workflows not only accelerates innovation but also addresses critical issues such as risk management, resource optimization, and the development of resilient urban environments. As cities worldwide invest in smart infrastructure, expertise at this intersection is increasingly sought after by both academia and industry.
Project Details
The position is based in Dr. Minghui Cheng’s group at the Department of Civil & Architectural Engineering, University of Miami. Dr. Cheng is an assistant professor with a robust background in systems engineering, having completed postdoctoral work at Cornell University. He is actively involved with the Task Group 1 of the ASCE Technical Council on Life-Cycle Performance, Safety, and Reliability, underscoring his commitment to advancing research in civil infrastructure resilience.
The group’s research portfolio includes:
– Application of LLMs and VLMs for advanced structural and finite element analysis.
– Development of uncertainty quantification methods and optimization via surrogate modeling.
– Implementation of digital twin-enabled solutions for smart cities and infrastructure systems.
This opportunity is open to both PhD and Postdoctoral candidates, with full financial support including tuition and stipends. The postdoctoral position is available for immediate start, while PhD applications are reviewed on a rolling basis.
Candidate Profile
Ideal candidates for this position should bring a strong foundation in civil engineering or closely related fields.
For the PhD role:
– Applicants must hold a Bachelor’s or Master’s degree in civil engineering or a related discipline.
– International applicants whose first language is not English will need to provide TOEFL or IELTS scores.
For the Postdoc role:
– A completed PhD in civil engineering or a related field is required.
Preferred qualifications for both levels include:
– Proficiency in Matlab or Python programming.
– Experience in machine learning and uncertainty quantification.
– A passion for interdisciplinary research at the interface of engineering and AI.
Applicants should demonstrate enthusiasm for innovative research, strong analytical skills, and the ability to work collaboratively in a diverse academic setting.
Application Process
To apply for this position, interested candidates should prepare the following:
– For PhD applicants: Submit a CV and transcript, and use the email subject line “CAE PhD Application – Your Name”. You are encouraged to include a brief statement describing your research interests, relevant experiences, course projects, skills, or career goals.
– For Postdoc applicants: Submit a CV, transcript, and a research statement, using the subject line “CAE Postdoc Application – Your Name”.
Please refer to the official advertisement for application details.
For more information and to access the original announcement, visit:
https://www.linkedin.com/posts/minghui-cheng_we-are-recruiting-a-fully-funded-phd-student-share-7446975391296253952-0VzF
Conclusion
This is an exceptional opportunity to join a leading research group at the University of Miami and contribute to pioneering work at the nexus of civil engineering and artificial intelligence. If you are driven by the desire to shape the future of smart cities and infrastructure systems, consider applying for this fully funded position. Stay tuned for similar opportunities and take the next step in your academic journey.
Questions & Answers
Question: What makes the University of Miami an attractive destination for international researchers?
The University of Miami offers a multicultural and inclusive environment, outstanding research facilities, and is located in a globally connected city. Its high ranking and commitment to innovation make it an ideal place for academic and professional growth.
Question: How does AI enhance civil engineering research in this context?
AI and machine learning enable the automation and optimization of complex engineering tasks such as structural analysis, risk assessment, and infrastructure monitoring, leading to smarter, safer, and more resilient cities.
Question: What background should successful applicants have?
Applicants should have a strong academic background in civil engineering or a related field, programming skills (preferably in Matlab or Python), and some experience or interest in AI and machine learning applications.
Question: Is financial support available for both PhD and Postdoc positions?
Yes, both positions offer full financial support, including tuition and stipends.
Want to calculate your PhD admission chances? Try it here:
https://phdfinder.com/phd_admission_chance_calculator/
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