CIFRE PhD Position: Implementation and Optimization of Quantum Algorithms for the many-body problem on Silicon Spin Qubits: From Solver Selection to Realistic Noisy Execution

• You will explore innovative approaches to adapt quantum algorithms such as Variational Quantum Eigensolver, Quantum Phase Estimation and/or Quantum Subspace methods to the constraints of silicon-based quantum processors,¹ with a particular emphasis on scalability, error mitigation, and resource efficiency^2–4
• You will involve theoretical developments, numerical simulations, and, if possible, experimental validation on available quantum devices.
• You will contribute to the practical application of quantum computing in the field of materials science and quantum chemistry, with potential impacts on the design of new materials and the understanding of complex quantum systems.

The PhD student will benefit from a stimulating research environment, with access to state-of-the-art facilities and expertise from both Quobly, IPCMS and LOMA. The position is fully funded for three years, with a competitive CIFRE salary. The successful candidate will be based primarily on Grenoble, with regular interactions with the LOMA and IPCMS teams.

• You hold a master’s degree in quantum/condensed-matter physics or quantum/theoretical chemistry, with a strong background in quantum mechanics and a demonstrated interest in quantum computing
• Proficiency in Python programming is essential, as the project will heavily rely on numerical simulations and the development of custom software tools. Experience with quantum computing frameworks (e.g., Qiskit, Cirq, or PennyLane) or quantum chemistry software (e.g., OpenFermion, psi4) will be considered a significant advantage.
• You’re curious and enthusiastic
• You have an R&D mindset

Applications should include a detailed CV, a cover letter outlining the candidate’s motivation and relevant experience, academic transcripts, and references. The selection process will begin immediately and continue until the position is filled. The expected start date is flexible, with a preference for January 1^st, 2027.

1. Vermersch, B. et al. The SpinPulse library for transpilation and noise-accurate simulation of spin qubit quantum computers. Preprint at https://doi.org/10.48550/arXiv.2601.10435 (2026).
2. Akande, H. A., Perrin, A., Senjean, B. & Saubanere, M. Variational Quantum Subspace Construction via Symmetry-Preserving Cost Functions. Phys. Rev. A 112, 032623 (2025).
3. Oumarou, O., Ollitrault, P. J., Polla, S. & Gogolin, C. Optimizing and Comparing Quantum Resources of Statistical Phase Estimation and Krylov Subspace Diagonalization. Preprint at https://doi.org/10.48550/arXiv.2603.15552 (2026).
4. Rammal, H. et al. Orthogonal Quantum Krylov Diagonalisation. Preprint at https://doi.org/10.48550/arXiv.2607.09476 (2026).