At CERN, the European Organisation for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature.
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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 to save 750 kHz 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.
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.
What we offer
A monthly net stipend of either 6,372 or 7,004 Swiss Francs per month 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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