What you'll do
The Event Filter (EF) is part of the ATLAS Trigger and Data Acquisition (TDAQ) system and consists of a multi-threaded asynchronous processing farm of commodity servers (CPUs with or without accelerators) running a subset of offline-like reconstruction algorithms together with menu-driven event selection.
The high-luminosity conditions expected during Phase-II operations introduce significant challenges for object and event reconstruction algorithms planned for the EF, particularly for track reconstruction. The recent definition of the EF farm as a heterogeneous architecture combining CPUs and GPUs opens new opportunities for deploying machine learning models within the EF tracking workflow.
You will be part of the CERN ATLAS team and will contribute to research into the application of ML techniques for track reconstruction at the HL-LHC, with the goal of identifying and exploring the most promising approaches for deployment in the ATLAS EF tracking. The position is part of the Next Generation Trigger programme.
Your responsibilities
- Conduct research on machine learning (ML) and AI-based approaches for track reconstruction, with a focus on the applicability and performance of these methods in the high pile-up environment of the HL-LHC.
- Investigate and benchmark novel ML-based tracking algorithms and their integration into the ACTS-based EF tracking workflow.
- Contribute to studies of both physics performance and computational performance of the different configurations under study.
- This role includes team supervision responsibilities.
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Your profile
- Understanding of tracking challenges in high track density environments, such as at the High-Luminosity LHC.
- Experience in the development and application of machine learning or deep learning methods in a physics or scientific computing context.
- Hands-on experience in the development of offline and/or online reconstruction software.
- Ability to lead teams and define directions.
- Your studies focused on PhD in Particle Physics / CS (or a related field).
Your skills
- Machine learning and deep learning frameworks.
- Experience with ML inference deployment.
- Knowledge of ML model training, evaluation, and optimisation, including hyperparameter tuning and performance benchmarking.
- Programming languages: C++ and Python, including software development workflows (Git, Jira).
- Experience with large-scale scientific software frameworks (e.g. ACTS, Athena) is considered an asset.
- Spoken and written English, with a commitment to learn French.
Employment conditions
- Stand-by duty, when required by the needs of the Organization.
- Work during nights, Sundays and official holidays, when required by the needs of the Organization.
Global Benefits at CERN
Let's get you ready
Be sure to meet the eligibility criteria
- By 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.
- You have never had a CERN fellow or graduate contract before.
- Please pay attention to the additional criteria and requirements for this specific position and mentioned above.
You will need these documents to complete your application
- Your CV (English or French)
- A copy of your most relevant diploma or a certificate of achievement from your school (if you don't yet have your paper diploma)
- Any document you consider relevant to your application