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Postdoctoral position in "Hybrid quantum algorithms for time series analysis"

Job Summary

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 time series analysis. This includes, among others, exploring and developing more efficient algorithms for forecasting, 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.

Job Description

It's required a PhD in quantum computing or quantum-inspired numerical simulation methods

The research will be carried at the DIPC group of Prof. Román Orús, and in collaboration with the research and services teams of Multiverse Computing.

Duration: 1 year (possibility to extend up to 3 years)

Target start date: 01/09/2023

Funds: This project has received funding from the MCIN program “Severo Ochoa”, under reference AEI/ CEX2018-000867-S.

Benefits

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