Haoran Li

Dr. Haoran Li is recruiting a fully funded PhD student to join his research group in the Department of Civil & Environmental Engineering at Lamar University , with a start date of Fall 2026 or Spring 2027 . The position sits at the intersection of civil engineering , environmental engineering , artificial intelligence , machine learning , life cycle assessment (LCA) , life cycle cost analysis (LCCA) , digital twins , infrastructure resilience , and climate-resilient infrastructure . The group works with state DOTs, FHWA, and industry partners on large-scale infrastructure problems. Research topics include AI- and data-driven infrastructure performance prediction, LCA/LCCA of transportation infrastructure, digital twin systems for monitoring and management, climate-resilient design under extreme weather, physics-informed and ML-based surrogate modeling, and sustainable materials/low-carbon construction strategies. The opening is fully funded and includes a tuition waiver , monthly stipend , and benefits . Applicants should have a strong academic background and research motivation. A B.S. or M.S. in Civil/Environmental Engineering, Mechanical Engineering, Computer Science, or a related field is preferred. Preferred skills include Python, MATLAB, or R; experience with PyTorch, TensorFlow, or scikit-learn; familiarity with ABAQUS, ANSYS, or similar finite element tools; and prior experience writing academic papers. Good written and verbal English communication skills are required, and international applicants should include English proficiency test scores. To apply, email the requested materials directly to Dr. Li. No formal deadline is stated in the post, so interested candidates should apply as soon as possible for consideration for the Fall 2026 or Spring 2027 intake.

Fully funded PhD opportunity in Civil and Environmental Engineering at Lamar University (Beaumont, Texas, USA) with Dr. Haoran Li . The position starts in Fall 2026 or Spring 2027 and is aimed at highly motivated doctoral applicants interested in research at the intersection of civil engineering, environmental engineering, and data-driven methods. Research focus includes AI- and data-driven infrastructure performance prediction, life cycle assessment (LCA) and life cycle cost analysis (LCCA) of infrastructure, digital twin systems for intelligent infrastructure monitoring and management, climate-resilient infrastructure design under extreme weather events, physics-informed and ML-based surrogate modeling, and sustainable/low-carbon construction strategies. Funding is explicitly stated as fully funded and includes a tuition waiver, monthly stipend, and other benefits. Eligibility highlights : B.S. or M.S. preferred in Civil/Environmental Engineering, Mechanical Engineering, Computer Science, or a related field; strong academic record; genuine motivation for research; good written and verbal English communication skills. Preferred skills include Python, MATLAB, or R; experience with PyTorch, TensorFlow, or scikit-learn; background in pavement, structural, geotechnical, or finite element analysis; familiarity with ABAQUS/ANSYS; and experience writing/publishing academic papers. International applicants should include English proficiency test scores. How to apply : email Dr. Li with the subject line “[Doctoral Application] – Your Name,” along with a current CV, unofficial transcripts, and a brief statement of research experience and interest.

Dr. Haoran Li is recruiting a fully funded PhD student to join the Department of Civil & Environmental Engineering at Lamar University , with a start date of Fall 2026 or Spring 2027 . The position sits at the intersection of civil engineering , environmental engineering , artificial intelligence , machine learning , life cycle assessment , life cycle cost analysis , digital twins , and climate-resilient infrastructure . The research group works with state DOTs, FHWA, and industry partners on infrastructure problems at scale. Research topics include AI- and data-driven infrastructure performance prediction, LCA/LCCA of transportation infrastructure, digital twin systems for infrastructure monitoring and management, climate-resilient design under extreme weather, physics-informed and ML-based surrogate modeling, and sustainable materials / low-carbon construction strategies. Funding is explicitly stated as fully funded , including a tuition waiver , monthly stipend , and benefits . Applicants should ideally have a background in civil/environmental engineering, computer science, mechanical engineering, or a related field. Strong academic performance, research motivation, English communication skills, and programming ability in Python, MATLAB, or R are preferred. Experience with machine learning tools, finite element analysis software, and academic publishing is also valued. To apply, email Dr. Li with a CV, unofficial transcripts, and a brief statement of research experience and interest. Use the subject line [Doctoral Application] – Your Name .

Fully funded PhD opportunity in Civil and Environmental Engineering at Lamar University (Beaumont, Texas) with a start date of Fall 2026 or Spring 2027 . The position is with Dr. Haoran Li , an incoming Assistant Professor whose research spans AI-driven infrastructure modeling, life-cycle assessment, digital twins, climate-resilient infrastructure, surrogate modeling, and sustainable construction materials. Research topics include: - AI- and data-driven infrastructure performance prediction - Life cycle assessment (LCA) and life cycle cost analysis (LCCA) - Digital twin systems for intelligent infrastructure monitoring and management - Climate-resilient infrastructure design under extreme weather events - Physics-informed and ML-based surrogate modeling - Sustainable materials and low-carbon construction strategies Applicants should have a B.S. or M.S. preferred in Civil/Environmental Engineering, Mechanical Engineering, Computer Science, or a related field. Strong academic performance, research motivation, and good English communication skills are required. Preferred experience includes Python/MATLAB/R, machine learning tools such as PyTorch, TensorFlow, or scikit-learn, finite element analysis software (ABAQUS/ANSYS), and prior academic writing or publishing experience. The position is described as fully funded and includes a tuition waiver , monthly stipend , and other benefits. Interested candidates should email Dr. Li with a CV, unofficial transcripts, English proficiency scores if applicable, and a brief statement of research experience and interests.