Technical Students for Next Generation Trigger Project 2026

What you'll do

In the coming upgrade to the Trigger system of the CMS Experiment many machine learning algorithms are being developed which will use low-level detector information to make decisions on whether to keep data or not. These algorithms will be exposed to a dynamic inference environment that will not only differ from their training environments but evolve over time as the detector conditions change. In the context of the Next Generation Trigger project you will explore continual learning approaches to incrementally updating trigger algorithms with new data specifically focusing on decision tree-based algorithms. The project will explore changing environments in the CMS detector as well as designing novel ways of training and updating decision trees. There will be opportunity to explore the implementation of these continual learning training techniques within the wider CMS trigger ML training infrastructure.

Your responsibilities

• Develop an understanding of implementing machine learning in dynamic environments, including the impact on output quality and methods to mitigate these effects.
• Acquire experience in developing and applying machine learning for the CMS trigger system, including fast machine learning and the techniques required to design trigger algorithms.
• Acquire experience in Python programming and code development within larger teams, including machine learning operations (MLOps) and ML infrastructure.

Your profile

• You are currently studying in Applied Physics, Engineering Physics or a related field.
• You are required or encouraged by your university to complete a practical training period.
• You are eager to develop your skills through on-the-job learning.
• You enjoy teamwork and learning from others in a collaborative setting.

Your skills

• A good understanding of applied physics fundamentals relevant to your studies.
• Curiosity, precision and a proactive attitude towards learning.
• Good communication skills and ability to work effectively in a multicultural team.