Data Analyst Beam Instrumentation; SY-BI-SW--GRAP

Job Description

As an experienced Data Analyst with a solid background in physics, you will join the team responsible for the LHC Longitudinal Density Monitor (commonly known as the BSRL: Beam Synchrotron Radiation Longitudinal monitor) within the Beam Instrumentation Group.

In this role, you will lead the work on the online and offline data processing pipelines, which are fully implemented in Python. The analysis results from this instrument are mission‑critical, directly impacting the calibration of the LHC experiments, facilitating the troubleshooting of operational issues, and enabling detailed beam physics analysis.

Additionally, you will play an important role in R&D and optimisation, conducting advanced studies to shape the upcoming upgrades of the BSRL instrument.

• Lead the redesign and optimisation of the current online and offline Python data analysis software for the BSRL instrument to ensure scalability, performance and reproducibility.
• Develop specialised offline analysis routines using BSRL data, cross‑correlating with other beam instrumentation where necessary, to meet the requirements of stakeholders.
• Extend the online and offline diagnostics tools, architecting automated notification systems to detect early signs of instrument degradation, anomalies, or malfunctions.
• Design and implement the specific software tools, calibration routines, and data pipelines required for the rapid commissioning of the renovated system after the Long Shutdown 3 (LS3).
• Contribute to the validation and performance verification of the associated upgraded hardware planned for deployment during LS3.
• Evaluate and benchmark different upgrade scenarios for LS3 by combining advanced data analysis of historical run data with physics‑based simulation techniques.

• Proven background in the advanced analysis of complex experimental data, preferably from physics or large‑scale scientific installations.
• Extensive experience in software development with a strong emphasis on clean, maintainable code.
• Basic experience in Monte Carlo‑based physics simulation techniques.
• Basic experience with laboratory work.

• In‑depth knowledge of advanced statistical methods, data modelling, and data analysis techniques applied to scientific datasets.
• Proven proficiency in Python, including familiarity with the standard scientific stack (such as Num Py, Pandas, Sci Py, etc.) for high‑performance processing.
• Knowledge of version control systems (Git/Git Hub) and continuous integration and deployment (CI/CD).
• Basic knowledge of photon counting techniques would be an advantage.
• Spoken and written English, with a commitment to learn French.

• You are a national of a CERN Member or Associate Member State.
• You have a professional background in Applied Physics, Data Analytics (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:
24.08.2026 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-December-2026.

This position involves:

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

Job reference: SY-BI-SW--GRAP.

Field of work:
Data Science & Data Analytics.

Benchmark job: 200140 - Applied Physicist.

• A monthly stipend between  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.