PhD Fellowship in Novel Methods of Demolition Waste Recognition and Classification
Join an international PhD programme developing multimodal sensing and machine learning for circular economy waste management.
Best for:Best for researchers with a background in computer vision, sensor fusion, or machine learning interested in environmental engineering applications.
Overview
The Czech Technical University in Prague is recruiting a PhD student for the PICTUS International PhD Programme. This project focuses on creating innovative, real-time systems for the recognition and classification of construction and demolition waste. The successful candidate will work with a multimodal sensing framework, integrating visible/infrared cameras, LiDAR, and Time-of-Flight sensors. The research aims to advance circular economy practices by optimizing material sorting through advanced machine learning and mechanical handling integration. This is a 48-month, full-time employment opportunity.
What you'll do
- Develop and implement multimodal sensing frameworks for waste identification.
- Design and train machine learning models for real-time material classification.
- Integrate sensor data from visible, NIR/SWIR, LiDAR, and ToF sources.
- Collaborate on the design of mechanical sorting technologies for recycling workflows.
- Conduct research in non-laboratory, real-world demolition environments.
- Participate in international secondments as part of the PhD training.
Requirements
Degree required: Master Degree or equivalent
Degree offered: PhD
Language: English; good proficiency required.
Instruction: English
- Strong background in machine learning and data processing.
- Experience with computer vision or sensor-based systems.
- Proficiency in English (good level).
- Ability to develop independent research proposals.
- Must meet the eligibility criteria for the PICTUS PhD Fellowship Programme.
- Must hold a Master's degree or equivalent.
Funding & terms
How to apply
Deadline: 2026-12-03 (Europe/Brussels)
Candidates must prepare a research proposal based on the provided list of topics. Applications must be submitted via the dedicated electronic form, including all required documentation.
- Research proposal
- CV
- Academic transcripts
Contact
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