Deep Learning Developer (IT-CE-CDS-2026-137-GRAP)

Foundation models represent one of the most powerful and promising advancements in Deep Learning, and their application to scientific domains is a rapidly evolving area of research. At CERN's IT-CE group, we are exploring the development of a foundation model tailored to particle physics: one capable of interpreting the behavior of particles within High Energy Physics (HEP) detectors and supporting a wide range of tasks relevant to experimental data processing. This work is carried out in close collaboration with a multidisciplinary team of experts from leading institutes across Europe in the context of TURING, a EC funded project .  As a successful candidate, you will contribute to the design and training of transformer-based architectures using data from calorimeters, specialised detectors that measure particle energy in collider experiments. Your work will involve investigating methodologies such as self-supervised learning to enable multi-task capabilities, while optimising for computational efficiency. We are looking for candidates with a strong background in Computer Science or a closely related field. Experience with Deep Learning, transformer models, or scientific data is highly desirable. This position is available immediately.

- Take an active role within the TURING project, leading the performance evaluation and use case validation tasks. - Developing a robust prototype capable of generalising across multiple detector use cases. - Contributing to tightening the collaborations with the CERN experimental physics community on the topic of foundation models for HEP.

- PhD in Data Science, Mathematics or Physics. - Proven experience developing, training, and deploying deep learning models in production environments, with hands-on expertise in neural network architectures, large-scale data processing, model optimisation, and performance evaluation.

- Strong proficiency in Python and deep learning frameworks (PyTorch and/or TensorFlow), machine learning algorithms, data analysis libraries (NumPy, Pandas), GPU-based training, software engineering best practices, Git version control, Docker, and MLOps tools for experiment tracking and model deployment. - Spoken and written English, with a commitment to learn French. Eligibility criteria: - You are a national of a CERN Member or Associate Member State . - You have a professional background in Data Science, Mathematics or Physics (or a related field) and have either: - a Master's degree with 2 to 6 years of post-graduation professional experience; - or a PhD with no more than 3 years of post-graduation professional experience. - You have never had a CERN fellow or graduate contract before.