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Graph Embedding for Quantum Optimization Internship

Forum 'Stages' - Sujet créé le 24/11/2023 par Wesley Coelho (388 vues)


Le 24/11/2023 par Wesley Coelho :

About Pasqal

 

PASQAL designs and develops Quantum Processing Units (QPUs) and associated software tools. Our innovative technology enables us to address use cases that are currently beyond the reach of the most powerful supercomputers; these cases can concern industrial application challenges as well as fundamental science needs. 

In addition to the exceptional computing power they provide, QPUs are highly energy efficient and will contribute to a significant reduction in the carbon footprint of the HPC industry.


Job Description

Graphs are used in a vast spectrum of fields. In particular, several combinatorial problems either are or can be defined on graphs, and are of particular relevance for Quantum Computing. Among the quantum computing platforms, neutral atoms are particularly well suited to solving these combinatorial graph problems. In fact, the Ising Hamiltonian which governs the behavior of the qubits is closely related to the cost function to be minimized.

Solving the problems is then equivalent to finding the ground state of the system, which can be achieved by adiabatic annealing. In recent years, the field of quantum computation has been focused on designing algorithms and hardware that can provide an advantage over classical computers. This advantage can take the form of more accurate results, a faster convergence, or even a lower energy consumption. These solutions are developed on very different platforms, using a wide range of technologies. One of the most prominent one is based on Rydberg neutral atoms, where an analog approach can be applied: as opposed to the case of digital quantum computing, the quantum operations are not divided into discrete consecutive steps (gates) but are rather the result of a time-dependent control of the Hamiltonian acting upon the qubits.

For this project, we will focus our attention on solving hard combinatorial graph problems, such as the Maximum Independent Set and related problems. By proposing new exact and heuristic approaches to better embed a given graph onto an atom register, we aim to improve the performance of current quantum algorithms proposed by PASQAL.

About you

You are preparing your Master's degree in Operations Research or related fields and have the following assets: 

Hard skills: 

  • Experience with at least one of the following programing languages: C, C++, Python, CUDA, Julia
  • Experience with linear and non-linear solvers such as Cplex, Baron, Gurobi, GLPK, IPOP
  • Strong taste for Applied Mathematics and graphs, and a keen interest in deep tech and new technologies
  • Good practices in algorithms development and numerical simulations
  • Report / documentation writing

Notions of quantum computing, atomic physics and optics are not mandatory but highly appreciated.

 Soft skills: 

  • English fluency 
  • Autonomy 
  • Proactivity 
  • Curious 
  • Team spirit 

If you think this position is for you, please send us your CV : https://careers.pasqal.com/jobs/3393040-graph-embedding-for-quantum-optimization-internship 


What we offer

  • Beautiful brand new offices in Massy
  • Type of contract : 6-months internship
  • A dynamic and close-knit international team
  • A key role in a growing start-up
  • Free time to train and go to conferences/meetups

Recruitment process

  • A 10-minute phose screen
  • A home assignment
  • A home assignment debrief and technical interview with our Hiring Managers
  • A 30-minute interview with one of our Talent Acquisition Specialist 

PASQAL is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace, as inclusion and diversity are essential to achieving our mission. We encourage applications from all qualified candidates, regardless of gender, ethnicity, age, religion or sexual orientation.

 

 







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