PhD position on algorithms for near term quantum (NISQ) computers

Occupation: Doktorand
Employer: Chalmers Tekniska Högskola AB
Workplace location: Göteborg, Västra Götalands län, Sverige
Last application date: 2022-08-31
Publication date: 2022-06-29

Prerequisites

Work experiences: Doktorand;



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Presentation:


This is a call for a PhD position in the Data Science and AI division at the Department of Computer Science and Engineering, Chalmers University of Technology.

Information about the project
This project is part of QuantumStack, a 5-year project funded by the Swedish Foundation for Strategic Research, with the aim of developing a full software stack for programming quantum computers. The project is integrated with the Wallenberg Centre for Quantum Technology (WACQT), a 12-year, billion-SEK initiative started in 2018 with the purpose of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer. Our ambitious goal at Chalmers is to build this quantum computer with 100 superconducting qubits and to apply it to real computational problems that cannot be efficiently solved on a conventional computer. Such computationally hard problems are found, e.g., in optimization, quantum chemistry, materials science, machine learning, etc.

This position is related to developing algorithms for solving useful tasks on noisy intermediate scale quantum (NISQ) computers i.e. quantum computers composed of hundreds of noisy qubits, i.e. qubits that are not error-corrected, and therefore perform imperfect operations in a limited coherence time. Recently there has been a lot of interest in such algorithms to solve problems in optimization, machine learning and quantum simulation. The Ph.D. project will focus on developing such algorithms and exploring both their advantages and limitations compared to classical algorithms running on conventional computers.

The project is funded by SSF (https://strategiska.se/en/) under their call for "Future Software Systems", see this (in Swedish): https://framtidensforskning.se/2022/06/17/framtidens-mjukvarusystem/

Major responsibilities
Your main responsibility as a PhD student is to pursue your doctoral studies within the framework of the outlined research project. You will be enrolled in a graduate program in the Department of Computer Science and Engineering. You are expected to develop your own ideas and communicate scientific results orally as well as in written form. In addition, the position includes 20% departmental work, mostly as a teaching assistant in Chalmers' undergraduate and masters-level courses or performing other departmental tasks.

Required qualifications
*MSc in Computer Science and Engineering, Physics, Mathematics, or related fields
*Excellent communication skills in written and spoken English

Desired qualifications: 
* Ability to program in high level languages such as Python or C.
* Strobg background in linear algebra, probability and statistics.
* Experience with quantum computing

We value a collaborative attitude and an interest in working both in teams and independently. Self-motivation, attention to detail, and a problem-solving analytical ability are important personal qualities for this position.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg. 
Read more about working at Chalmers and our benefits for employees. Chalmers offers Swedish courses.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.

Application procedure: Read more and apply HERE

Application deadline: 31st August, 2022

For questions, please contact:
Professor Devdatt Dubhashi, CSE/DSAI
E-mail: dubhashi@chalmers.se

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. *** 




 

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