M2 CIFRE Internship: Quantum Algorithms on Silicon Spins

Quobly; Grenoble; On-site; EUR 13,000 - 17,000; Full time

Benefits offered by this job

Work from home up to four days perweek

75% bus/train transport passes covered

Job summary

Quobly in Grenoble offers a 6-month M2 internship aiming at CIFRE PhD continuation in quantum algorithms for the many-body problem on silicon spin qubits. The position blends quantum computing and quantum chemistry, with co-supervision from CNRS LOMA (Bordeaux) and IPCMS (Strasbourg).

The project progresses through literature study, implementation of a Krylov-type subspace method with QPE, noisy simulations on SpinPulse, and reporting results to the collaborating teams.

Qualifications

• Enrolled in a Master 2 or final-year engineering program in quantum or condensed-matter physics, or in quantum or theoretical chemistry, or quantum information.
• Solid background in quantum mechanics and genuine interest in quantum computing.
• Comfort with Python programming and numerical simulations.

Responsibilities

• Study the literature on variational and subspace-based quantum algorithms and get familiar with SpinPulse and standard quantum computing tools.
• Implement a quantum subspace (Krylov-type) method plus QPE for small benchmark systems.
• Simulate execution on silicon spin qubits with SpinPulse; quantify impact of noise on accuracy and resources.
• Write a report and present results to Quobly, LOMA and IPCMS teams.

Education

Master 2 student

Engineering final year

Tools

Qiskit

Cirq

PennyLane

OpenFermion

PySCF

Psi4

Python

Job description

Quobly in Grenoble offers a 6-month M2 internship aiming at CIFRE PhD continuation in quantum algorithms for the many-body problem on silicon spin qubits. The position blends quantum computing and quantum chemistry, with co-supervision from CNRS LOMA (Bordeaux) and IPCMS (Strasbourg).

The project progresses through literature study, implementation of a Krylov-type subspace method with QPE, noisy simulations on SpinPulse, and reporting results to the collaborating teams.