- Location
- Paris
- Workplace
- Hybrid
- Type
- Internship
- Department
- Platform
- Seniority
- Internship
- Education
- Master
- Source
- Lever
Description
Alice & Bob is developing the first universal, fault-tolerant quantum computer to solve the world’s hardest problems.
The quantum computer we envision building is based on a new kind of superconducting qubit: the Schrödinger cat qubit 🐈⬛. In comparison to other superconducting platforms, cat qubits have the astonishing ability to implement quantum error correction autonomously!
We're a diverse team of 250+ brilliant minds from over 35 countries united by a single goal: to revolutionise computing with a practical fault-tolerant quantum machine. Are you ready to take on unprecedented challenges and contribute to revolutionising technology? Join us, and let's shape the future of quantum computing together!
PURPOSE OF THE ROLE
The intern will investigate whether high-fidelity simulations, fast surrogate models and experimental data can be combined into a digital twin of Alice & Bob's cat-qubit devices. As these devices scale up, the predictive accuracy of physical and numerical models becomes harder to guarantee, and measurements from chips in our cryostats can validate and refine the models.
Data assimilation is the general framework that combines simulations and experimental data: it updates model states from measurements, accounting for model and measurement uncertainties, so the models stay accurate as new observations arrive. High-fidelity simulations, however, are costly, which limits how many the team can run. Surrogate and multi-fidelity models ease this limit by delivering high-fidelity results at a fraction of the cost, and they integrate into data assimilation. Faster and more accurate simulations then let the team explore more scenarios within the same compute budget.
The intern will build a proof of concept on a representative use case, defined jointly with the team during the first weeks. The deliverables are a validated prototype and the methodological and technical building blocks of a future digital-twin framework. Reporting to the Scientific Computational Engineer, the intern will work with the Simulation Engine team and with the teams producing experimental data.
The intern will investigate whether high-fidelity simulations, fast surrogate models and experimental data can be combined into a digital twin of Alice & Bob's cat-qubit devices. As these devices scale up, the predictive accuracy of physical and numerical models becomes harder to guarantee, and measurements from chips in our cryostats can validate and refine the models.
Data assimilation is the general framework that combines simulations and experimental data: it updates model states from measurements, accounting for model and measurement uncertainties, so the models stay accurate as new observations arrive. High-fidelity simulations, however, are costly, which limits how many the team can run. Surrogate and multi-fidelity models ease this limit by delivering high-fidelity results at a fraction of the cost, and they integrate into data assimilation. Faster and more accurate simulations then let the team explore more scenarios within the same compute budget.
The intern will build a proof of concept on a representative use case, defined jointly with the team during the first weeks. The deliverables are a validated prototype and the methodological and technical building blocks of a future digital-twin framework. Reporting to the Scientific Computational Engineer, the intern will work with the Simulation Engine team and with the teams producing experimental data.
This internship will start in February 2027 for a duration of 6 months!
Skills
PythonCI/CDDeep LearningTensorFlowPyTorchGit