Join us to push the boundaries of real-time Machine Learning (ML) in one of the most demanding computing environments in the world. You will develop cutting-edge ML models for the CMS Level-1 Trigger - an ultra-low-latency, FPGA-based system responsible for selecting the most interesting LHC collisions in real-time.
You will help design the next generation of trigger algorithms for the High Luminosity LHC era by co-training ML models across different systems to maximise physics performance while optimising information flow, bandwidth, and on-device resource usage. This includes developing and scaling MLOps workflows, integrating ML models into FPGAs, and delivering demonstrators that validate full-chain performance from training and physics performance to on-hardware deployment.
This position is part of the NextGen Triggers (NGT) project, a 5-year collaboration between LHC experiments and the CERN Research and Computing Departments. The project leverages innovative Artificial Intelligence technologies and high-performance computing architectures to enhance trigger selection, data processing, and theoretical interpretation for LHC experiments. The insights gained will inform future detector development, data flows, and theoretical tools.
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