Postdoc in Integrating in-line Vision Technology and AI for Improved Concrete Production
Core
Develop a deep learning-based image analysis framework for in-line monitoring of concrete and its constituent materials using hyperspectral imaging data to enable real-time prediction of physicochemical behavior and performance.
Role type
Postdoc in computer vision and deep learning for industrial process monitoring
Builds
Deep learning models, predictive algorithms, and a graphical user interface (GUI) for non-expert users
Domain
Construction materials technology / Industrial AI / Hyperspectral imaging
Deliverable
production ML models | product features
Required skills
deep learning, computer vision, hyperspectral imaging data processing, in-line process monitoring, experimental research in concrete characterization
Preferred skills
concrete characterization, experimental research
Technologies
deep learning frameworks, hyperspectral imaging systems
Responsibilities
Implement and optimize deep learning models for quality control; develop predictive algorithms based on hyperspectral inputs; develop a GUI for model application; collaborate with interdisciplinary team; disseminate research via publications and conferences; teach and supervise PhD and MSc student projects
Seniority
Postdoc (18 months), research-focused
