Optimization & ML Intern: Algorithms in C++/Python

Synopsys, Inc.; Villeurbanne; Sur place; EUR 13 000 - 20 000; Plein temps

Résumé du poste

Synopsys, Inc. seeks a Master’s student for a 6-month internship in Lyon, in-office. You will work on optimization algorithms, metamodel techniques, and machine learning within the optiSLang team, developing prototypes in C++ and Python and validating them with comprehensive benchmarks.

You’ll collaborate with cross-functional teams, document results, and explore cutting-edge numerical methods and ML tools in a real-world engineering context.

Qualifications

• Pursuing a Master’s in Engineering, Mathematics, Physics, or Computer Science
• Familiar with numerical methods and a genuine interest in machine learning, optimization, and statistics
• C++ and Python programming skills; comfortable in Windows/Linux environments
• Strong written and spoken English communication
• Experience with surrogate modeling and related libraries (Matlab, Python, ML/libs)
• Knowledge of Python/Pandas, NumPy, SciPy is desirable

Responsabilités

• Conduct R&D on optimization algorithms, metamodel techniques, and ML applications
• Develop prototypes in C++/Python and integrate into software libraries
• Create test cases and benchmarks to evaluate algorithm performance
• Collaborate with cross-functional teams, gather requirements, and document findings
• Explore numerical methods and ML with hands-on simulation software

Connaissances

C++

Python

Machine learning

Numerical methods

Windows/Linux

English

Formation

Master's degree in Engineering, Mathematics, Physics, or Computer Science

Outils

Matlab

TensorFlow

PyTorch

Scikit-learn

Theano

Description du poste

Synopsys, Inc. seeks a Master’s student for a 6-month internship in Lyon, in-office. You will work on optimization algorithms, metamodel techniques, and machine learning within the optiSLang team, developing prototypes in C++ and Python and validating them with comprehensive benchmarks.

You’ll collaborate with cross-functional teams, document results, and explore cutting-edge numerical methods and ML tools in a real-world engineering context.