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PASQAL

Machine Learning Internship – Rydberg-Based Quantum Simulators

PASQAL

Intern in machine learning for Rydberg quantum simulators at Pasqal, developing hybrid quantum-classical approaches with hands-on experience in quantum processing units.

Posted 5/31/2026internshipMassy • 🇫🇷 FranceEntry LevelWebsite

Tech Stack

Tools & technologies
PythonPyTorchTensorflow

About the role

Key responsibilities & impact
  • Develop and train Neural Quantum States (NQS + VMC), with pretraining of the NQS on datasets generated by the QPU.
  • Benchmark this approach against established numerical methods (e.g., exact diagonalization, standard VMC, tensor networks) and against raw QPU data.
  • Apply NQS to represent observables and many-body wavefunctions of magnetic Hamiltonians.
  • Contribute to internal tools and publications.

Requirements

What you’ll need
  • Master’s or PhD student in quantum many-body physics.
  • Proficiency in one or more programming languages such as Python or Julia.
  • Demonstrated experience with machine learning methods applied to quantum many-body systems (e.g., neural quantum states, supervised and unsupervised ML, kernel methods).
  • Experience with numerical methods for quantum spin systems (e.g., exact diagonalization and variational Monte Carlo).
  • Familiarity with scientific computing frameworks (e.g., JAX, PyTorch, TensorFlow).
  • Experience working in high-performance computing (HPC) environments.
  • Ability to work collaboratively in a research team.
  • Strong communication skills in English.

Benefits

Comp & perks
  • Hands-on experience with Pasqal’s analog QPU and emulator stack used to model such devices.
  • The opportunity to learn key aspects of Pasqal’s quantum hardware.
  • Mentorship from a multidisciplinary team (quantum many-body physics, machine learning, materials science).

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
Neural Quantum StatesVariational Monte Carlomachine learningnumerical methodsquantum spin systemsPythonJuliaJAXPyTorchTensorFlow
Soft Skills
collaborative workstrong communication skills