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Algorithmic Screening of Materials for Rydberg Quantum Simulators internship HF

Pasqal


Job Location:

Palaiseau - France

Salary: Not provided by the employer
Posted: 29 May 2026 (30+ days ago)
Application Deadline: 26 August 2026
Vacancies: 1 Vacancy
The job posting is outdated and position may be filled

Job Summary

About the team

The Quantum material department at Pasqal develop hybrid quantum classical algorithms with applications in material science and quantum many-body physics and that can be run on Pasqal neutral atom quantum processing units.

We are offering an internship position to work on developing an algorithmic pipeline to identify materials compatible with Rydberg quantum simulators. This multidisciplinary project will involve different aspects such as accessing material databases developing screening procedures many-body physics.

Mission

  • Survey and access existing materials databases (e.g. Materials Project C2DB).

  • Design and implement a screening pipeline for materials compatible with Rydberg simulators.

  • Map candidate materials onto effective spin Hamiltonians (e.g. Ising XY).

  • Collaborate with the team on validating candidates via emulators.

  • Document and benchmark the pipeline.

  • Contribute to internal tools and publications.

What we offer

  • Hands-on experience with Pasqals analog QPU and emulator stack.

  • The opportunity to learn aspects related to material science as well as Pasqals quantum hardware.

  • Mentorship from a multidisciplinary team (quantum many-body physics machine learning materials science).

Required Qualifications

Hard Skills

  • Master or PhD student in quantum many-body physics.

  • Proficiency in one or more programming languages such as Python.

Nice to Have

  • Experience with many-body physics

  • Familiarity with magnetism and/or effective spin Hamiltonians (e.g. Heisenberg Ising XY)

  • Basic familiarity with electronic-structure methods (DFT) or solid-state physics

  • Familiarity with scientific computing frameworks (e.g. JAX PyTorch TensorFlow)

  • Experience with machine learning methods

  • Experience handling structured/scientific data (databases APIs JSON HDF5)

Soft Skills

  • Ability to work collaboratively in a research team.

  • Strong communication skills in English.

Logistics

  • Duration: 6 months

  • Expected starting date: second semester of 2026

  • Location: Massy (France)


About Company

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Joining Pasqal will give you the opportunity to take an active part in the rapid development of a DeepTech scale-up at the forefront of the second quantum revolution. You will be directly involved in one of the biggest challenges shaping the technological landscape of the 21st century ... View more

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