Data Reduction Physicist (EP-CMS-TDQ-2026-146-GRAP)

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.

- 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.

- 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.

- 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.