Postdoc position in Quantum Machine Learning

Job type: 


Application deadline: 

Wednesday, October 14, 2020

The position is part of the project “Quantum Computing Platform for NISQ Era Commercial Applications” funded by Innovate UK. This is a multidisciplinary collaborative project involving stakeholders in industry (Rigetti and Standard Chartered) and academy (University of Edinburgh). The successful candidate will join a team focused on conducting leading research into quantum computation for emerging scalable devices. This full time, fixed term post is available from 1 November 2020 until 31 May 2023

The successful candidate should have a PhD in Computer Science or Physics, and a strong background on either classical or quantum machine learning. Candidates without a track record in quantum computing are eligible, provided that they're interested in near term applications of quantum computing.

Salary: £41,526 - £49,553
Informal enquiries to Prof. Elham Kashefi:
Closing date is 5pm (GMT) on 14th October 2020
Apply directly through the platform:

Job Purpose

The search for an application of near-term quantum devices is widespread. Quantum Machine Learning is touted as a potential utilisation of such devices, particularly those which are out of the reach of the simulation capabilities of classical computers. We explore generative Quantum Learning that cannot, in the worst case, and up to suitable notions of error, be simulated efficiently by a classical device. We are also focused on specific use cases in Finance, Cryptanalysis, Optimal Compiling for such models and compare the capabilities of quantum versus classical models for such tasks.