Data Reduction Physicist in Genève

ppThe 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. /p h3Your responsibilities /h3 ul liDesign next-generation data structures that push the limits of data reduction while preserving physics performance and analysis flexibility. /li liEnsure all formats are accelerator-native (e.g., structure-of-arrays, SoA) and optimised for high-throughput GPU processing. /li liBuild an end-to-end framework to rigorously quantify the impact of lossy compression, with clear metrics, reference analyses, and automated regression tests. /li liBenchmark compression/decompression under realistic workloads: CPU/GPU cost, I/O throughput, memory footprint, and latency. /li liAdvance lossless compression, leveraging R3-reconstructed objects and pioneering AI/ML techniques. /li liImprove raw data structure to achieve higher compressibility and faster data access. /li /ul h3Be sure to meet the eligibility criteria /h3 ul liBy the application deadline, you have a master’s degree with 2 to 6 years of professional experience since graduation or a PhD with a maximum of 3 years of professional experience since graduation. You are not eligible with only a bachelor’s degree. /li liYou have never had a CERN fellow or graduate contract before. /li liPlease pay attention to the additional criteria and requirements for this specific position and mentioned above. /li /ul /p #J-18808-Ljbffr