Generative AI for Scientific Data Internship (Hybrid)

Quobly; Grenoble; On-site; EUR 10,000 - 15,000; Full time

Job summary

Quobly, based in Grenoble, is seeking a motivated intern to join the Software team and advance the intersection of generative AI, computer vision, and quantum data. You will collaborate with physicists and engineers, implement Python-based data pipelines, and train models on GPUs to generate realistic scientific data.

The role emphasizes code quality, reproducibility, and learning ability, with a 6-month commitment in a dynamic research environment in the French Alps.

Qualifications

• Final-year engineering student or Master’s candidate in AI, data science, computer science, computer vision, physics or related field.
• Proficient in Python with a solid foundation in ML/DL.
• Care about code quality: readable, maintainable, reproducible code.
• Curious, rigorous, and capable of analyzing complex problems and testing approaches.
• Experience with PyTorch, CV, generative models, synthetic data or Git is a plus.
• Prior knowledge of quantum computing is not required.

Responsibilities

• Study physics-based simulators and compare simulated vs. experimental data.
• Explore image generation, synthetic data and domain adaptation.
• Develop Python pipelines for data prep, model training, and evaluation.
• Train and compare models on GPUs using PyTorch or similar.
• Collaborate with physicists and engineers to assess realism and consistency.
• Document results, limitations and next steps, and integrate prototypes into tools.

Skills

Python

Machine Learning

Deep Learning

English communication

Education

Final-year engineering degree or Master’s in AI/Data Science/CS/CV/Physics

Tools

PyTorch

Git

CUDA

Job description

Quobly, based in Grenoble, is seeking a motivated intern to join the Software team and advance the intersection of generative AI, computer vision, and quantum data. You will collaborate with physicists and engineers, implement Python-based data pipelines, and train models on GPUs to generate realistic scientific data.

The role emphasizes code quality, reproducibility, and learning ability, with a 6-month commitment in a dynamic research environment in the French Alps.