Improve QBoost for production - ON-1097
Project type: ResearchDesired discipline(s): Computer science, Mathematical Sciences
Company: Multiverse Computing
Project Length: Longer than 1 year
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Toronto, ON, Canada
No. of positions: 1
Desired education level: Undergraduate/BachelorMaster'sPhD
Open to applicants registered at an institution outside of Canada: No
About the company:
Multiverse is a well funded deep-tech Canadian company. We are one of the few world companies working with Quantum Computing.
We provide hyper-efficient software for companies from the financial industry wanting to gain an edge with quantum computing and artificial intelligence. Our main verticals are fraud detection, credit scoring assessment, and financial optimization.
Our team of experts is world-renowned for innovative approaches to intractable financial and macro-economics problems. We work with quantum hardware and quantum inspired methods to build machine learning solutions which exceed the predictive power of the current best solutions.
We are applying to Mitacs to allow us to expand our R&D team in Canada to tackle problems of huge commercial impact and expand our expertise.
Describe the project.:
Explore different cost functions to address the imbalance problem.
• Explore new methods for weak classifier selection and training.
• Bring the code up to production standards
Required expertise/skills:
Bachelors or Masters or Phd in Computer Science, Machine Learning and Python programming.
