9 Student English-speaking jobs in Grenoble

Internship focused on extending the GLLiM framework for scalable, expressive surrogate models in large-scale inverse problems. Tasks involve developing and implementing extensions in C++ and Python for high-dimensional remote-sensing applications.

Internship focusing on evaluating Graph Neural Networks coupled with radar sensor data. The role involves implementing and proposing innovative methods for processing radar data using AI algorithms.

Internship focused on calibrating 3D multiphysics COMSOL models of Solid-Oxide-Electrolyzer-Cells (SOEC). The role involves using Optimal Experimental Design (OED) to address parameter correlation during model calibration.

Web Development Intern to build web solutions using Vue.js and Nuxt 3. Responsibilities include creating components, developing documentation, and enhancing web interfaces. Requires CS/Web Dev studies, HTML/CSS/JS knowledge, and Git familiarity.

Internship to compute free-energy landscapes for lithiated graphite using DFT and machine learning potentials. Tasks include Monte Carlo and molecular dynamics simulations to inform continuum electrode models. Requires skills in atomistic simulations and statistical physics.

Study state-of-the-art methods for modeling Voltage Controlled Filters (VCF). Test and compare non-linear solvers, from iterative to machine learning, for zero-delay feedback modeling. Requires strong DSP and electrical engineering knowledge.

Support e-commerce performance by managing distributor advertising campaigns, enhancing conversion rates through CRM collaboration, and coordinating content production. Requires a Master's in marketing and e-commerce experience.

Internship to adapt deep learning models for audio effects into real-time CPU implementations. Tasks include C++ implementation using the Arturia framework and exploring model compression techniques. Requires knowledge of DSP and ML.

Internship to explore LLM approaches modifying traditional static analysis for source code security evaluation. Define and experiment with new LLM-based methods, studying LLM complementarity with tools like Frama-C. Requires computer engineering background and knowledge of static analysis.