Postdoc in Multimodal AI and Computational Modeling for Scalable Disaster Monitoring and Resilience Lehigh University in United States

Lehigh University’s Center for Catastrophe Modeling and Resilience is recruiting a Postdoctoral Research Associate in Multimodal AI and Computational Modeling for Scalable Disaster Monitoring and Resilience.

This postdoc is centered on computer science, civil engineering, machine learning, deep learning, remote sensing, geospatial AI, catastrophe modeling, computer vision, and data analytics. The researcher will work with Professor Maryam Rahnemoonfar and the center on AI-driven disaster damage assessment, catastrophe-aware resilience modeling, multimodal geospatial data analysis, physics-informed machine learning, uncertainty quantification, and scalable pre- and post-disaster analysis.

Responsibilities include independent and collaborative research, building AI pipelines for large-scale disaster monitoring, publishing in peer-reviewed journals and conferences, contributing to proposals and interdisciplinary collaborations, and mentoring students. The role also includes participation in seminars, workshops, and broader center activities.

Eligibility requires a doctoral degree in Civil Engineering, Computer Science, Data Science, or a closely related field completed by the start date, plus strong skills in Python and frameworks such as PyTorch or TensorFlow. Experience in disaster modeling, catastrophe modeling, resilience analytics, or geospatial risk assessment is preferred, along with a publication record and strong communication skills.

This is a full-time, one-year position with possible renewal depending on performance and funding. Compensation is competitive and includes benefits. Lehigh also highlights healthcare, tuition remission, and retirement savings opportunities.

Application deadline: August 1, 2026, or until filled. Applicants should submit a cover letter, CV, research plan, and three recommendation letters through the university application system.