Supply Chain Optimization Using Quantum Computing - ON-647

Project type: Research
Desired discipline(s): Computer science, Mathematical Sciences, Mathematics, Physics / Astronomy, Natural Sciences
Company: ZebraKet Ltd
Project Length: Flexible
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Toronto, ON, Canada; Canada
No. of positions: 1
Desired education level: PhDPostdoctoral fellow
Open to applicants registered at an institution outside of Canada: No

About the company: 

ZebraKet has started in CDL, Toronto, Canada and has earned a reputation for being awarded as the third place in Hackathon 2021 at CDL Toronto. We are building novel optimization tools and quantum algorithms for the supply chain industry with the aim of pushing the boundary of possible quantum computing applications in the industry. Our streamlined integrated optimization solution could reduce 7-10% of overhead costs of retail companies. 

Describe the project.: 

We are building novel optimization tools and quantum algorithms for the supply chain industry. We aim to develop demand prediction and optimization tools for the supply chain using quantum computing, annealing, and quantum-inspired technologies.

ZebraKet provides plug-and-play quantum software for optimized inventory stock level recommendations in the supply chain industry. Maintaining the right inventory level and purchasing schedule is critical to reducing tied-up capital, as companies struggle to meet fluctuating demand resulting in surplus or shortage of goods. Our solution intends to provide improved results compared to traditional methods, and faster and cheaper implementation compared to competitors using AI and ML methods.

Required expertise/skills: 

  • Programming: Python, C++, Java
  • Machine learning
  • Quantum Machine learning
  • Quantum annealing and D-wave hybrid solvers
  • QAOA and QUBO problems
  • Artificial intelligent
  • Mathematical optimization models – Convex optimization

We are looking for an expert in quantum computing (QC) and mathematics. He/she should have rich experience in QC, D-Wave hybrid solvers, and Quantum Annealing. The expert in quantum computing should be familiar with optimization and mathematical modeling techniques. The core responsibility of the expert will be leading the mathematical modeling and development into quantum computing, annealing, and quantum-inspired technologies. Having a good background in quantum machine learning is an advantage.

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