Digital Twin & Surrogate Modelling Intern M/F (Quantum Computing)
Контакты
Формат работы
hybrid
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
France
pythongitci cdstartupjaxscientific computinguncertainty quantificationnumerical analysisquantum physicsdata assimilationreduced order modelling
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TL;DR
Digital Twin & Surrogate Modelling Intern M/F (Quantum Computing): Building a validated proof of concept that combines high-fidelity simulations, surrogate models, and experimental data into a digital twin for cat-qubit devices with an accent on data assimilation, uncertainty quantification, and scientific software. Focus on developing reduced-order models, comparing simulations with experimental measurements, and implementing reusable Python/JAX components for future digital-twin frameworks.
Location: Hybrid, Paris, France
Company
Alice & Bob is developing a universal, fault-tolerant quantum computer based on superconducting Schrödinger cat qubits with autonomous quantum error correction.
What you will do
Develop fast surrogate models and assess their accuracy, uncertainty, and domain of validity for high-fidelity simulations.
Implement data assimilation methods that connect experimental measurements with simulations and quantify model and measurement uncertainties.
Run the team's high-fidelity simulation tools, interpret results, and compare simulation outputs with experimental data.
Write clean, tested, and documented Python/JAX software and contribute reusable components to a future digital-twin framework.
Present results and methodological choices while collaborating with simulation, experimental, and design teams.
Requirements
Final year of a Master's degree (M2) or engineering school in physics, applied mathematics, or scientific computing.
Proficient English.
Interest in scientific software, the ability to structure an open-ended problem, work autonomously, and keep the team informed.
Background in engineering and solid foundations in numerical analysis and numerical methods.
Knowledge of data assimilation methods, including uncertainty quantification, and reduced-order modelling.
Experience with open-source scientific simulation software.
Proficiency in Python with strong experience in JAX.
Good software engineering practices, including Git, testing, documentation, CI/CD, and verification and validation (V&V).
Rigour, autonomy, curiosity, and the ability to explain technical choices clearly. No professional experience is required; coursework and research projects can provide relevant skills.
Nice to have
A previous internship or research project in scientific computing or numerical simulation.
Statistics or Bayesian inference.
Experience with PyTorch or TensorFlow.
Deep learning, quantum physics, or circuit engineering.
Rigorous use of agentic workflows for scientific research and implementation.
Culture & Benefits
One day off per month.
Half of transportation costs covered according to French law.
Meal vouchers through Swile.
Fully equipped and regularly stocked kitchen.
International team of more than 250 people from over 35 countries, with opportunities to share knowledge, innovate, and develop new ideas.
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