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.

Your responsibilities:

• 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.

Your profile:

• 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.

Skills:

• 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.

Job closing date: 15.09.2026 at 23:59 CEST.

Contract duration: 24 months, with a possible extension up to 36 months maximum.

Working hours: 40 hours per week

Job flexibility: Hybrid

Target start date: 01-November-2026

This position involves:

• Stand-by duty, when required by the needs of the Organization.
• Work during nights, Sundays and official holidays, when required by the needs of the Organization.

Job reference: IT-CE-CDS-2026-137-GRAP

Field of work: Data Science, AI & Analytics

Benchmark job: 100020 - Research Physicist

Global Benefits

• A monthly stipend between 6372-7004 Swiss Francs per month (tax free) depending on your degree.
• 30 days of paid leave per year plus 2 weeks annual closure.
• Coverage by CERN’s comprehensive health insurance scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund.
• Family, child and infant monthly allowances depending on your individual circumstances.
• A relocation package (installation grant and travel expenses) depending on your individual circumstances.
• Possibility to extend your contract up to 36 months.
• On-the-job and formal training including language classes.

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