Data Processing/Artificial Intelligence Engineer and Applications in Particle Physics H/F
Role details
Job location
Tech stack
Job description
Irfu is recruiting an engineer specialized in data processing and artificial intelligence (AI) / deep learning as part of the development of a foundation model dedicated to particle physics to address the scientific and technological challenges of the High-Luminosity Large Hadron Collider (HL-LHC).
Scheduled to begin operation around 2029, the HL-LHC will increase the integrated luminosity of the current LHC by a factor of ten, producing unprecedented volumes of data (on the order of several exabytes over its lifetime). This major evolution makes the development of new AI and algorithmic approaches essential, particularly for event reconstruction and physics analysis. Scientific objectives include Higgs boson physics, searches for physics beyond the Standard Model, heavy-flavour physics and QCD phenomenology.
Within this context, Irfu is developing a foundation model trained on large volumes of simulated and/or real data from the ATLAS, CMS and LHCb experiments to enable efficient transfer learning (fine-tuning) for a wide range of downstream physics tasks. This approach is directly inspired by the success of large language models (LLMs) and vision foundation models.
You will join a multidisciplinary team composed of particle physicists, scientific computing engineers and machine learning researchers. Main responsibilities:
- Design, train and evaluate AI model architectures adapted to particle physics data.
- Develop self-supervised learning strategies using simulated and real LHC datasets.
- Develop data processing pipelines, experiment tracking tools and physics performance benchmarks.
- Contribute to scientific and technical documentation, publications and presentations at international conferences.
Requirements
PhD in computational physics, signal processing/AI or a related field.
- Good knowledge of particle physics and/or nuclear physics.
- Strong background in large-scale data processing and machine learning/deep learning (neural networks, transformers, etc.).
- Proficiency with Python AI/ML frameworks (PyTorch) and the scientific Python ecosystem (NumPy, Pandas, Scikit-learn, etc.).
- Experience with collaborative software development tools such as Git and CI/CD.
- Experience working in high-performance computing environments (HPC, GPU clusters, SLURM).
Additional assets: * Knowledge of HEP data formats and tools such as ROOT and HDF5.
- Experience with particle-physics-specific architectures (ParticleNet, PELICAN, Particle Transformer, JetGPT, OmniJet, etc.).
- Experience publishing scientific papers or contributing to HEP-ML open-source software.
Personal skills:
- Ability to work effectively in multidisciplinary teams and proactively propose new ideas.
- Pragmatic, rigorous and able to tackle complex problems under multiple constraints.
- Curious, adaptable, autonomous and possessing excellent interpersonal skills.
- Excellent written and spoken communication skills in both French and English, including technical English.
You enjoy working in a multidisciplinary team and know how to be proactive.
You are pragmatic and know how to take initiative. Your analytical skills, rigour and ability to take a step back allow you to calmly tackle complex problems under multiple constraints (deadlines to meet, major technical challenges).
You are curious, adaptable and autonomous, and have good interpersonal skills.
You have excellent written and oral communication skills in both French and English and are proficient in technical English (comprehension and written and oral expression).