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Postdoctoral position in "Hybrid quantum algorithms for partial differential equations"

Job Summary

We are currently accepting applications for the above mentioned position. This is a unique opportunity for junior researchers with a recent PhD degree in Physics or related fields to join one of DIPC’s high-profile research teams.

Job Description

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) to solve Partial Differential Equations (PDEs). This includes, among others, exploring and developing more efficient algorithms for fluid dynamics, 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 CUCO project.

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

Contract 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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