Digital Twin & Surrogate Modelling Intern

Alice & Bob

. Build fast surrogate approximations of high-fidelity simulations .

Posted 10/19/2026internshipParis • FranceEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates proficiency in Python and JAX for developing surrogate models and implementing data assimilation methods, with a strong foundation in numerical analysis and scientific computing. Capable of collaborating with cross-functional teams to deliver validated prototypes and contribute to a digital-twin framework.

Highest-signal resume keywords

Proficiency In PythonExperience With JAXKnowledge Of Data Assimilation MethodsSolid Foundations In Numerical AnalysisGood Software Engineering Practices

ATS Keywords

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Hard Skills

Numerical MethodsUncertainty QuantificationReduced-Order ModellingOpen-Source Scientific Simulation SoftwareVersion Control (Git)TestingDocumentationCI/CDVerification & Validation (V&V)Statistics

Soft Skills

RigourAutonomyCuriosityAbility To Explain Technical Choices Clearly

Tools & Technologies

PythonJAXPyTorchTensorFlow

Industry Keywords

Scientific ComputingNumerical SimulationDigital-Twin FrameworkExperimental DataCircuit EngineeringQuantum Physics

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Build fast surrogate approximations of high-fidelity simulations
Assess surrogate-model accuracy, uncertainty, and domain of validity
Implement data assimilation methods linking measurements to simulations
Quantify model and measurement uncertainties
Use high-fidelity simulation tools to generate and interpret results
Compare simulation outputs with experimental data
Write clean, tested, and documented Python/JAX code within the team codebase
Contribute reusable components for a digital-twin framework
Present results and methodological choices to the team
Collaborate with experimental and design teams to understand data and needs
Build a proof of concept for a representative use case
Deliver a validated prototype and methodological and technical building blocks for a future digital-twin framework
Report to the Scientific Computational Engineer and work with the Simulation Engine and experimental-data teams

Requirements

What you’ll need

Final year of a Master's degree (M2) or engineering school in physics, applied mathematics or scientific computing
Proficient in English
No professional experience required; coursework and research projects can supply the required skills
Previous internship or research project in scientific computing or numerical simulation appreciated
Background in engineering
Solid foundations in numerical analysis and numerical methods
Knowledge of data assimilation methods, including uncertainty quantification
Knowledge of reduced-order modelling
Experience with open-source scientific simulation software
Proficiency in Python, with strong experience in JAX
Good software engineering practices, including version control (Git), testing, documentation, CI/CD, and verification & validation (V&V)
Rigour, autonomy, curiosity, and ability to explain technical choices clearly
Nice to have: Statistics or Bayesian inference
Nice to have: Experience with PyTorch or TensorFlow
Nice to have: Deep learning
Nice to have: Quantum physics
Nice to have: Circuit engineering
Nice to have: Rigorous use of agentic workflows for scientific research and implementation

Benefits

Comp & perks

1 day off per month
Half of transportation cost coverage (as per French law)
Meal vouchers with Swile
Access to a fully equipped and regularly stocked kitchen
Space to grow and develop new ideas