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Data Reduction Physicist (EP-CMG-2026-13-GRAP)
European Council for Nuclear Research (CERN)
CERN
Full-time
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Posted 4 hours ago
Job Description

Job Description

The NGT Real-time Reconstruction Revolution will transform the CMS High-Level Trigger into an offline-quality reconstruction facility processing up to 750 kHz of events. To make this sustainable, you will lead the design of two complementary data tiers: a low-level reconstructed format that enables trigger rates several times higher than conventional raw-data output while preserving the the option for future reprocessing, and a compact analysis format to save the full 750 kHz stream of online reconstructed events.

Your responsibilities

  • Design next-generation data structures that push the limits of data reduction while preserving physics performance and analysis flexibility.
  • Ensure all formats are accelerator-native (e.g., structure-of-arrays, SoA) and optimised for high-throughput GPU processing.
  • Build an end-to-end framework to rigorously quantify the impact of lossy compression, with clear metrics, reference analyses, and automated regression tests.
  • Benchmark compression/decompression under realistic workloads: CPU/GPU cost, I/O throughput, memory footprint, and latency.
  • Advance lossless compression, leveraging R³-reconstructed objects and pioneering AI/ML techniques.
  • Improve raw data structure to achieve higher compressibility and faster data access.

Your profile

  • Demonstrated contributions to trigger and/or reconstruction in HEP (or comparable high-throughput scientific software).
  • Practical understanding of of end-to-end HEP experiment operations, from detector readout to reconstruction, calibrations, datasets, and final physics results.
  • Experience working in a large international collaboration (code review, CI/CD, documentation) is a plus.
  • Knowledge with LHC experiments and their data formats is a plus.
  • Expertise in data compression techniques is a plus. (lossless and/or lossy).
  • Experience applying AI/ML methods (e.g., autoencoders) to data reduction is a plus.
  • Proficiency in GPU programming and heterogeneous computing is a plus.

Skills

  • High proficiency in C++, Python, and ROOT.
  • Solid understanding of event reconstruction, including calibrations and commonly used data formats in HEP.
  • 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 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.

Additional Information

Job closing date: 19.02.2026 at 23:59 CET.

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-March-2026

Job reference: EP-CMG-2026-13-GRAP

Field of work: Applied Physics

Benchmark job: 200140 - Applied 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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