PhD Researcher in Identification for Circular Construction

Job description

• Conduct research on digital inventory methods for building stock in circular construction, focusing on methods to capture relevant parameters to assess buildings condition, safety, quality, and environmental sustainability.
• Collaborate with interdisciplinary team members to develop and implement digital solutions for large-scale reuse of building materials.
• Use surveying, reality capture (photogrammetry, LiDAR, etc.), computer vision, and machine learning techniques to identify and catalog building components during demolition processes.
• Analyze data collected from construction sites to predict material reuse potential, optimize reuse strategies and minimize waste.
• Contribute to the development of scientific publications based on research findings and participate in conferences and site visits.
• Work closely with industry partners and stakeholders to ensure the practical application of research outcomes in real-world construction projects.

Your profile

• Master's degree in a relevant field such as Computer Science, Civil Engineering, Architecture, or a related discipline.
• Strong background in digital technologies, reality capture, machine learning, and/or computer vision.
• Experience with data analysis, programming languages (e.g., Python, R), and software tools commonly used in construction research.
• Excellent communication skills and ability to work effectively in a collaborative research environment.
• Prior research experience in sustainable construction, circular economy, or related fields is desirable but not mandatory.