Applied Physicist

Job Posting Organization:
CERN, the European Organization for Nuclear Research, is a leading scientific research institution established in 195

• It is known for its groundbreaking work in particle physics and is home to the Large Hadron Collider (LHC), the world's largest and most powerful particle accelerator. CERN employs over 2,500 staff members and collaborates with thousands of scientists from around the globe, representing more than 100 nationalities. The organization operates in multiple countries and is dedicated to pushing the frontiers of science and technology, fostering an environment of innovation and collaboration.

Job Overview:
The position of Applied Physicist at CERN involves developing advanced Machine Learning (ML) models for the CMS Level-1 Trigger, which is a critical component of the LHC's data acquisition system. The role requires the candidate to engage in the design and training of ML models aimed at enhancing the physics selections of the CMS Phase-2 Level-1 Trigger. This includes optimizing information transport across a multi-algorithm system and integrating ML models into FPGA hardware. The successful candidate will be part of the NextGen Triggers (NGT) project, a collaborative effort that leverages cutting-edge AI technologies and high-performance computing to improve trigger selection and data processing for LHC experiments. The position also involves scaling MLOps workflows and delivering demonstrators that validate the performance of the developed models, making it essential for the candidate to have a strong background in both physics and machine learning.

Duties and Responsibilities:
The Applied Physicist will be responsible for designing and training ML models to enhance the physics selections of the CMS Phase-2 Level-1 Trigger. Key duties include:

• Developing, delivering, integrating, and testing ML models in FPGA environments, including RTL/HLS components and software emulators.
• Demonstrating physics performance improvements and presenting findings within the CMS collaboration, at CERN, and at international conferences.
• Designing and implementing MLOps practices to scale workflows for reproducible training, validation, and deployment of ML-based trigger algorithms.
• Collaborating with colleagues in CMS, CERN departments, and external research institutes focused on ML-for-Trigger research.
• Engaging in continuous learning and adaptation to new technologies and methodologies in the field of machine learning and physics data analysis.

Required Qualifications:
Candidates must possess a professional background in Physics or a related field. They should have experience in developing and applying Machine Learning algorithms specifically for physics or scientific data analysis. Familiarity with Fast ML and hardware-constrained ML techniques is advantageous. Knowledge of physics analysis methods and experience with Trigger and Data Acquisition systems, including hardware architectures, is essential. Practical experience with software development tools such as GitHub/GitLab, Continuous Integration, and MLOps is required. Basic knowledge of FPGA design, including HDLs (VHDL/Verilog) and/or High-Level Synthesis (C++), is also necessary.

Educational Background:
The ideal candidate should hold 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. Candidates must be nationals of a CERN Member or Associate Member State and should not have previously held a CERN fellow or graduate contract.

Experience:
The position requires candidates to have a solid background in Machine Learning, with practical experience in applying ML algorithms to physics or scientific data analysis. Familiarity with hardware-constrained ML techniques and knowledge of physics event reconstruction methods are highly desirable. Experience with Trigger and Data Acquisition systems, as well as software development practices, is crucial for success in this role.

Languages:
Fluency in spoken and written English is mandatory, and candidates should demonstrate a commitment to learning French, which is considered a valuable asset for the position.

Additional Notes:
The contract duration for this position is 24 months, with the possibility of extension up to a maximum of 36 months. The working hours are set at 40 hours per week, and the job offers a hybrid working model. The target start date for the position is April 1, 202

• The job reference is EP-CMG-OS-2025-260-GRAP. The position offers a competitive monthly stipend ranging from 6287 to 6911 Swiss Francs, which is tax-free, along with 30 days of paid leave per year and additional benefits such as comprehensive health insurance, family allowances, and a relocation package.