Postdoctoral position in "Hybrid quantum algorithms for pattern recognition"

The aim if this project is to explore new ideas in the field of quantum and quantum-inspired (tensor network) machine learning and optimization methods to develop hybrid algorithms (classical & quantum) for pattern recognition and artificial vision. This includes, among others, exploring and developing more efficient algorithms for anomaly detection, among others, improving the overall performance in time and energy cost, as well as in accuracy. The hybrid algorithms will make use of different QPUs in combination with state of the art Tensor Network methods. The research will be carried in collaboration with Multiverse Computing, in the context of the QCDI project.