Website Zapata Computing
We seek an exceptional researcher for a two-year industry postdoc position in the group of Alán Aspuru-Guzik at the University of Toronto and jointly with Zapata Computing. You will be the principal researcher in a three-way-collaboration with the University of Toronto, a Fortune 500 Company, and Zapata Computing. The project focuses on developing and testing quantum algorithms for combinatorial optimization and machine learning. A goal of the collaboration is the development of open-source software packages and publications in high-impact journals. You will play a vital role in advancing Zapata’s efforts in building algorithms for improving the pipelines of our industry clients.
Key responsibilities include:
- Developing and testing quantum algorithmic methods for combinatorial optimization and machine learning
- Communicating closely with industry clients to understand their needs
- Analyzing data and presenting analysis to team members and industry clients
- PhD in computer science, physics, mathematics, or a related discipline
- Experience with modern software languages such as Python or Julia
- Experience with basic concepts in machine learning such as classification, principal component analysis, and feature selection
- Familiarity with convex and non-convex optimization methods
- Experience with machine learning packages such as Scikit-Learn, Keras, or Tensorflow
- Expertise with software engineering basics such as version control and unit testing
- Expertise in quantum and/or quantum-inspired algorithms
Zapata is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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