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Data Scientist (TE-DPS-AIM-2026-76-GRAP)

CERN

Geneva, GENEVA, Switzerland permanent

Posted: March 30, 2026

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Quick Summary

Join CAFEIN platform team at CERN and help shape the next generation of federated AI technologies used in some of the world's most advanced scientific environments. Translate real-world challenges, medical data analysis, anomaly detection, com. Translate real-world challenges, medical data analysis, anomaly detection, com. Translate real-world challenges, medical data analysis, anomaly detection, com.

Job Description

Join the CAFEIN platform team at CERN and help shape the next generation of federated AI technologies used in some of the world's most advanced scientific environments.

In this role, you'll contribute to R&D on state-of-the-art machine learning, designing, implementing, and evaluating advanced algorithms end to end. The work spans large-scale data pipelines and applied solutions in medical AI, anomaly detection, and complex systems modelling from exploratory research through to deployment.

Your responsibilities

• Translate real-world challenges, medical data analysis, anomaly detection, complex systems modelling, into well-defined ML problems.
• Design, implement, and evaluate state-of-the-art ML models using Python and frameworks such as PyTorch, TensorFlow, JAX, scikit-learn, and Hugging Face.
• Contribute to the research and development of federated learning methods, agentic AI, and applied ML solutions for tabular, image and signal data.
• Develop applied ML solutions for diverse domains including medical imaging, anomaly detection, and predictive maintenance.
• Perform exploratory data analysis, feature engineering, and visualisation to support model development and identify new use cases.
• Document methods, write clear reports, publish findings, and communicate results within multidisciplinary R&D teams.
• This role includes team supervision responsibilities.

Your profile

• Strong background in machine learning, statistics, and data science fundamentals.
• Excellent proficiency in Python for ML research and experimentation, with hands-on experience with major frameworks and libraries (PyTorch, TensorFlow, JAX, scikit-learn, Hugging Face).
• Demonstrated experience designing, implementing, and evaluating state-of-the-art ML algorithms, including transformer-based and agentic architectures.
• Experience conducting ML experiments, benchmarking models, and interpreting results across diverse data modalities (tabular, medical imaging and signal data).
• Practical exposure to federated learning concepts and privacy-preserving or distributed ML approaches is a plus.
• Strong scientific mindset with a track record of reading, understanding, and contributing to research literature.
• Good communication skills to document methods, present results, and collaborate within multidisciplinary R&D teams.

Skills

• Expert knowledge of Python, deep learning frameworks (PyTorch, TensorFlow, JAX, Hugging Face), and machine learning algorithms.
• Professional knowledge of anomaly detection algorithms, LLMs, RAG systems, Generative AI, and agentic AI approaches.
• Professional knowledge of image segmentation techniques and Graph Neural Networks (GNNs).
• Familiarity with federated learning tools and distributed ML environments.
• Strong communication skills for documenting methods, presenting results, and collaborating in multidisciplinary R&D teams.
• Knowledge of particle accelerator systems or healthcare applications would be an advantage.
• 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, IT, Mathematics (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: 20.04.2026 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: Fully Onsite

Target start date: 01-July-2026

Job reference: TE-DPS-AIM-2026-76-GRAP

Field of work: Data Science & Data Analytics

Benchmark job: 200020 - Computing Engineer

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.

Overview of CERN - Discover a world where the impossible is made possible!

At CERN, the European Organization for Nuclear Research, we are pushing the frontiers of science and technology. Our groundbreaking work brings together not only physicists but also a diverse range of professionals from engineering, technical, scientific, and administrative fields. Together, we foster an environment where innovation and collaboration thrive.

Every day, we face exciting new challenges and opportunities to contribute to cutting-edge research that shapes our understanding of the universe. We meet these challenges through the diverse perspectives within our teams, ensuring every contribution is valued and driving our shared sense of inclusion and purpose. Diversity is a core value of CERN since its foundation, and it remains central to our mission and continued success.

If you are ready to be part of a dynamic, inclusive community pushing the boundaries of knowledge, CERN is the place where your curiosity and skills can thrive. Be part of our mission to uncover what lies at the heart of the universe! TAKE PART!

More information about us, here: careers.cern

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