Postdoctoral Research Fellow in Sustainable Construction

Post: Postdoctoral Research Fellow in Sustainable Construction

To lead advanced research on low-carbon concrete, geopolymer systems, and AI-optimized infrastructure for climate-resilient cities. The fellow will develop and evaluate innovative construction materials suited for the Gulf’s climate, integrate AI and machine learning for design optimization and lifecycle prediction, and contribute to the UAE’s low-carbon development goals.

• Design and evaluate sustainable concrete formulations, including geopolymer, seawater/sea-sand concrete, and LC³.
• Conduct experimental studies on mechanical, durability, and thermal properties under Gulf-specific environmental conditions.
• Use advanced lab equipment for full-scale structural testing and environmental exposure studies.
• Integrate AI/ML models for mix optimization, performance prediction, and lifecycle assessment.
• Publish research outcomes in leading peer-reviewed journals.
• Contribute to writing technical reports and grant deliverables.
• Mentor and collaborate with graduate students and junior researchers.
• Participate in project meetings and communicate findings to stakeholders.
• Participate in organizing conferences and workshops.

• PhD in Structural Engineering, Civil Engineering, Materials Science, or a closely related field.
• Strong track record in concrete mechanics, low‑carbon materials, and structural testing.
• Demonstrated publication record in high‑impact journals and conference proceedings.
• Advanced experimental techniques in concrete durability and strength testing.
• Familiarity with chloride ingress, carbonation, and heat/humidity exposure methods.
• Ability to work across interdisciplinary teams and support graduate student mentorship.
• Strong written and verbal communication skills in English.

• Background in sustainable construction in hot, humid, and coastal environments.
• Experience with integration of recycled aggregates and seawater systems.
• Proficiency in AI/ML tools for infrastructure optimization.
• Skilled in handling large datasets related to material and environmental analysis.

• Interested applicants should fill out this form.
• AUS alumni are encouraged to apply. Applicants who do not meet specified requirements will not be shortlisted. Only shortlisted candidates will be contacted.
• AUS is an equal opportunity employer. We adhere to a policy of making employment decisions without regard to race, color, age, gender, religion, national origin, disability or marital status. Opportunities for employment are based solely upon one’s qualifications.