Data Reduction Physicist

Lead the design of complementary data tiers for the CMS High-Level Trigger, creating accelerator-native formats and an end-to-end framework to measure compression impacts. The post advances lossless and lossy compression, benchmarks realistic CPU and GPU workloads, and uses AI or ML methods while preserving physics performance, reprocessing options and analysis flexibility.

• Design next-generation data structures for data reduction
• Build a framework to quantify lossy compression impacts
• Benchmark compression and decompression workloads
• Advance lossless compression and AI/ML techniques

• Master’s degree with 2 to 6 years of professional experience since graduation, or PhD with maximum 3 years
• Studies focused on Physics
• High proficiency in C++, Python, and ROOT
• Spoken and written English, with commitment to learn French

• Experience working in a large international collaboration is a plus
• Knowledge of LHC experiments and data formats is a plus

• C++
• Python
• ROOT
• Data compression
• GPU programming
• Event reconstruction

• C++
• Python
• ROOT