Quantum ML Intern: Rydberg-Based Simulators

Jobtailor

Massy

Sur place

EUR 30 000 - 54 000

Plein temps

14 jours+

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Résumé du poste

Jobtailor is seeking a Master’s or PhD student in quantum many-body physics to develop and train Neural Quantum States (NQS) and VMC, with pretraining on datasets generated by a QPU. You will join a collaborative research team in Massy, Île-de-France, working on state-of-the-art numerical experiments.

You will benchmark against exact diagonalization, standard VMC and tensor networks, and apply NQS to observables and wavefunctions of magnetic Hamiltonians.

Qualifications

  • Master’s or PhD student in quantum many-body physics.
  • Proficiency in Python or Julia.
  • Experience applying ML to quantum many-body systems.
  • Experience with numerical methods for quantum spin systems.
  • Familiarity with JAX, PyTorch or TensorFlow.
  • Experience working in HPC environments.
  • Ability to work collaboratively in a research team.
  • Strong communication skills in English.

Responsabilités

  • 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.

Connaissances

Python
Julia
Machine learning for quantum systems
HPC
Team collaboration
English communication

Formation

Master’s or PhD student in quantum many-body physics

Outils

JAX
PyTorch
TensorFlow
NumPy

Description du poste

Jobtailor is seeking a Master’s or PhD student in quantum many-body physics to develop and train Neural Quantum States (NQS) and VMC, with pretraining on datasets generated by a QPU. You will join a collaborative research team in Massy, Île-de-France, working on state-of-the-art numerical experiments.

You will benchmark against exact diagonalization, standard VMC and tensor networks, and apply NQS to observables and wavefunctions of magnetic Hamiltonians.

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