Hybrid ML & Analytical HW Performance Modeling Internship

CEA; Saclay; On-site; EUR 13,000 - 20,000; Part time

Job summary

CEA invites you to join LECA at Saclay for an internship focused on combining ML models with analytical HW performance predictions. You will work in a world-renowned research environment with access to state-of-the-art resources and opportunities to publish results.

The project aims to develop a hybrid modeling methodology balancing accuracy, transferability, and design-space exploration, with emphasis on Python/C++ and AI-driven EDA techniques.

Qualifications

• Master's degree or Engineering diploma required.
• Familiarity with AI, knowledge of computer architecture, proficiency in Python and C/C++, and experience with Git.
• Collaborative mindset and genuine curiosity.

Responsibilities

• Investigate hybrid performance modeling combining ML-driven data with analytical architectural models.
• Evaluate transferability across hardware generations with minimal retraining.
• Contribute to design-space exploration for efficient hardware development.

Skills

AI familiarity

Computer architecture

Python

C/C++

Git

Education

Master's degree or Engineering diploma

Tools

Python

C/C++

Git

Job description

CEA invites you to join LECA at Saclay for an internship focused on combining ML models with analytical HW performance predictions. You will work in a world-renowned research environment with access to state-of-the-art resources and opportunities to publish results.

The project aims to develop a hybrid modeling methodology balancing accuracy, transferability, and design-space exploration, with emphasis on Python/C++ and AI-driven EDA techniques.