Job Description

In this role, you will help develop advanced methods to compress deep learning models using low-rank and tensor-network techniques.

You will contribute to the pQuant open-source library, working with an interdisciplinary team to make AI models more efficient and scalable, conducting research and development activity as part of a heterogenous team of physicists and computer scientists.

Your responsibilities:

• Research and implement tensor-network methods for compressing neural networks.
• Explore low-rank approximations and their combination with knowledge-distillation techniques.
• Test and compare compression approaches on realistic datasets and applications.
• Contribute to the development, documentation, and maintenance of the pQuant open-source library.
• Work in an international, interdisciplinary team of scientists and software engineers.
• Share research outcomes through publications, presentations, and open-source contributions.

This role includes team supervision responsibilities.

Your profile:

• Expertise in deep learning, tensor networks.
• Experience in model compression techniques (knowledge distillation, pruning, quantization), FPGA programming, or hardware-aware AI deployment is highly desirable.

Skills:

• Advanced knowledge of Linear Algebra.
• Basic programming skills (Python).
• Experience with Machine Learning.
• Spoken and written English or French, with a commitment to learn the basics of the other language.

Eligibility criteria:

• You are a national of a CERN Member or Associate Member State.
• You have a professional background in Mathematics, Physics (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.

Additional Information

Job closing date: 06.01.2026 at 23:59 CET.

Contract duration: 24 months, with a possible extension up to 36 months maximum.

Working hours: 40 hours per week

Job flexibility: Hybrid

Target start date: 01-February-2026

This position involves:

• Work during nights, Sundays and official holidays, when required by the needs of the Organization.

Job reference: EP-SFT-2025-235-GRAP

Field of work: Data Science & Data Analytics

Benchmark job: 200140 - Applied Physicist

What we offer

• A monthly stipend ranging between 6287 and 6911 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.

About us

At CERN, the European Organization 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. Find out more on http://home.cern.

We are on a Quest. A Journey into discovery like no other. Bring your expertise to our unique work and develop your knowledge and skills at pace. Join world-class subject matter experts on unique projects, in a Quest for greater knowledge and deeper understanding.

Begin your CERN Quest. Take Part!

Diversity has been an integral part of CERN's mission since its foundation and is an established value of the Organization. Employing a diverse workforce is central to our success.