At CERN, the European Organisation for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature.
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Job description
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 aims to leverage 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.
Join our team in developing new firmware and software for the real-time data processing system of the Compact Muon Solenoid (CMS) experiment, a major detector at the Large Hadron Collider (LHC). The project involves upgrading the Level-1 (L1) trigger system to handle the high data rates expected in the future high-luminosity phase of the LHC. Additionally, we're exploring the implementation of a complementary system called L1 Data Scouting, which involves real-time data processing and analysis using FPGA-equipped boards.
Responsibilities:
Develop innovative unsupervised machine learning techniques, such as autoencoders, to:
Select events with an unbiased approach, enhancing sensitivity to unreachable parts of the phase space.
Reduce the L1-scouting dataset size through intelligent data compression while preserving downstream physics reach.
Collaborate effectively within a team, including colleagues at CERN collaborating institutes.
Present work at conferences/workshops at CERN and external venues.
Your profile
Skills and/or knowledge
Advanced knowledge in Machine Learning algorithms (boosted decision trees, neural networks) including Fast Machine Learning
Knowledge and application of physics analysis methods
Trigger and Data Acquisition systems, their hardware and associated tools
Software development platforms (e.g. github, gitlab), and continuous integration
Basic knowledge and application of FPGA programming including Hardware Description Languages and High Level Synthesis
Eligibility criteria:
You are a national of a CERN Member or Associate Member State. A limited number of positions are also available to candidates from Non-Member States.
You have a professional background in Physics or Computer Science (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.
What we offer
A monthly stipend ranging between 6,194 and 6,808 Swiss Francs per month (net of tax).
Coverage by CERN's comprehensive health scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund.
Depending on your individual circumstances: installation grant; family, child and infant allowances; payment of travel expenses at the beginning and end of contract.
30 days of paid leave per year.
On-the-job and formal training at CERN as well as in-house language courses for English and/or French.
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