Deep Learning Developer

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

• It is located in Geneva, Switzerland, and is known for its groundbreaking work in particle physics. CERN employs thousands of scientists, engineers, and support staff from over 100 countries, fostering a collaborative environment that encourages innovation and scientific discovery. The organization operates numerous research facilities and experiments, including the Large Hadron Collider, and is dedicated to pushing the frontiers of science and technology. Diversity and inclusion are core values at CERN, ensuring that every contribution is valued and that the organization continues to thrive in its mission to understand the universe.

Job Overview:
The Deep Learning Developer position at CERN's IT-CE group focuses on the development of a foundation model specifically designed for particle physics. This role involves interpreting particle behavior within High Energy Physics (HEP) detectors and supporting various tasks related to experimental data processing. The successful candidate will work closely with a multidisciplinary team of experts from leading European institutes as part of the TURING project, which is funded by the European Commission. The position requires a strong background in computer science or a related field, with a particular emphasis on deep learning and transformer models. The role is available immediately and offers an opportunity to contribute to cutting-edge research in a collaborative environment.

Duties and Responsibilities:
The primary responsibilities of the Deep Learning Developer include actively participating in the TURING project, leading performance evaluation and use case validation tasks, and developing a robust prototype that can generalize across multiple detector use cases. The candidate will also be responsible for enhancing collaborations with the CERN experimental physics community regarding foundation models for HEP. This involves designing and training transformer-based architectures using data from calorimeters, investigating methodologies such as self-supervised learning for multi-task capabilities, and optimizing for computational efficiency. The role may also require stand-by duty and work during nights, Sundays, and official holidays as needed by the organization.

Required Qualifications:
Candidates must possess a PhD in Data Science, Mathematics, or Physics, or a Master's degree with 2 to 6 years of post-graduation professional experience. Proven experience in developing, training, and deploying deep learning models in production environments is essential, along with hands-on expertise in neural network architectures, large-scale data processing, model optimization, and performance evaluation. Strong proficiency in Python and deep learning frameworks such as PyTorch and/or TensorFlow is required, as well as familiarity with machine learning algorithms, data analysis libraries (NumPy, Pandas), GPU-based training, software engineering best practices, Git version control, Docker, and MLOps tools for experiment tracking and model deployment.

Educational Background:
The educational background required for this position includes a PhD in Data Science, Mathematics, or Physics, or a Master's degree in a related field with relevant professional experience. Candidates should have a solid foundation in data science principles and practices, as well as a strong understanding of deep learning methodologies and their applications in scientific research.

Experience:
The position requires candidates to 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. Experience in developing and deploying deep learning models in production environments is crucial, as is familiarity with large-scale data processing and model optimization techniques.

Languages:
Fluency in spoken and written English is mandatory, and candidates should demonstrate a commitment to learning French. Proficiency in additional languages may be considered an asset but is not required for this 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, with a hybrid work flexibility option. The target start date for this position is November 1, 202

• The role includes a monthly stipend ranging from 6372 to 7004 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 depending on individual circumstances. On-the-job and formal training, including language classes, will also be provided.