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

CERN; Deutschland; Hybrid; EUR 76.000 - 83.000; Vollzeit

Benefits dieser Stelle

Monthly stipend 6,372–7,004 CHF (tax‑e

30 days leave + 2 weeks closure

Health insurance & pension

Relocation support

Language courses

Zusammenfassung

CERN's IT-CE group is building a foundation model tailored to particle physics to interpret detector data and support a range of scientific tasks. You will work within TURING, an EC-funded project, developing transformer-based architectures and exploring self-supervised learning for multi-task capabilities.

The role requires a PhD in Data Science, Mathematics, or Physics, with hands-on DL experience in production. English is essential; French learning is encouraged.

Qualifikationen

• PhD in Data Science, Mathematics or Physics as required.
• Experience developing, training and deploying deep learning models in production.

Aufgaben

• Lead performance evaluation and use case validation within the TURING project.
• Develop a robust prototype generalising across detector use cases.
• Contribute to collaborations with CERN experimental physics community on foundation models for HEP.

Kenntnisse

Python

PyTorch

TensorFlow

NumPy

Pandas

GPU Training

Git

Docker

MLOps

English

French (learn)

Ausbildung

PhD in Data Science/Mathematics/Physics

Master's degree + 2-6 years experience or PhD with <=3 years

Tools

Docker

Git

Jobbeschreibung

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 6372-7004Swiss 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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