Z Synergies Inc. – AI powered solar panel recycling & refurbishment - ON-1161

Project type: Innovation
Desired discipline(s): Engineering - other, Engineering, Computer science, Mathematical Sciences, Environmental sciences, Natural Sciences
Company: RAAS SYSTEMS Inc.
Project Length: Longer than 1 year
Preferred start date: 12/08/2025
Language requirement: English
Location(s): ON, Canada
No. of positions: 2
Desired education level: Master'sPhD
Open to applicants registered at an institution outside of Canada: No

About the company: 

Z Synergies Inc. is a Canadian cleantech venture (based by RAAS SYSTEMS INC.) developing the country’s first AI-powered solar panel recycling and refurbishment plant. Our mission is to address the growing environmental challenge of end-of-life photovoltaic (PV) waste by recovering high-value materials such as high-purity silicon, aluminum, glass, silver, and copper, and by refurbishing reusable panels for secondary markets.
Our technology integrates artificial intelligence, robotics, and industrial engineering to reduce recycling costs, increase material recovery rates, and significantly lower the lifecycle environmental footprint of solar energy. The proposed pilot facility aims to process tens of thousands of panels annually while supporting Canada’s Net-Zero 2050 targets and Ontario’s Circular Economy objectives.

We collaborate with municipalities, EPR programs, installers, utilities, and academic institutions to validate AI models, develop advanced processing techniques, and build a robust circular supply chain.

Describe the project.: 

This innovation project focuses on developing an AI-enhanced recycling and refurbishment process for end-of-life solar panels to support Z Synergies' upcoming pilot plant in Ontario. The project aims to develop computer-vision inspection tools, process-engineering models, and optimized material-recovery workflows for a next-generation cleantech recycling operation.

Goals:
• Design and train AI/computer vision models to classify panels for reuse or recycling.
• Create an optimized industrial engineering model for dismantling, delamination, silicon recovery, and material separation.
• Reduce costs and environmental impact compared to traditional shredding or landfilling.
• Conduct lab-scale validation of separation and refinement processes.
• Support techno-economic analysis (TEA) and lifecycle assessment (LCA).

Candidate Responsibilities:
• Literature review on PV recycling, AI inspection, and circular-economy models.
• Develop AI models using Python/TensorFlow/PyTorch.
• Create process-flow diagrams, simulations, and optimization algorithms.
• Assist in prototype development for dismantling/separation.
• Analyze environmental impact and recovery rates.

Methodologies:
Machine learning, computer vision, operations research, industrial engineering design, process modeling, simulation, and lab testing.

Required expertise/skills: 

Required Skills:

• Python (data processing, ML frameworks)
• Understanding of AI/ML & image recognition
• Industrial/process engineering knowledge
• Simulation & process modeling experience
• Strong research and analytical skills
• Strong technical writing skills

 

Assets:

• CAD experience
• Knowledge of PV systems & recycling
• LCA/TEA experience
• Robotics/automation familiarity