Computational Physicist ( Machine Learning and Optimal Control) (BE-CSS-DSB-2024-142-GRAE) | |
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Workplace | Geneva, Lake Geneva region, Switzerland |
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Computational Physicist ( Machine Learning and Optimal Control) (BE-CSS-DSB-2024-142-GRAE)
Job DescriptionYour responsibilitiesCERN has recently launched the Efficient Particle Accelerators (EPA) project to better exploit its accelerator complex in terms of reliability, efficiency, and beam performance. Alongside classical automation concepts, machine learning (ML) techniques have started playing a major role in realizing these goals. You will join the Data Science for Beam Operation (DSB) section within the Controls Software and Services (CSS) group. The DSB team is responsible for designing and implementing numerical optimization and ML algorithms to tackle previously intractable problems in machine operation. This includes delivering accurate, fast-executing online models and developing operational ML tools for CERN’s accelerator complex, alongside evolving the underlying frameworks. As part of an interdisciplinary team with expertise in accelerator physics and operation, ML and optimal control, as well as computer science, you will:
Your profile Skills and/or knowledge
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Additional InformationJob closing date: 10.10.2024 at 23:59h (midnight) CEST.Job reference: BE-CSS-DSB-2024-142-GRAE Contract duration: 24 months, with a possible extension up to 36 months maximum. Target start date: 01-November-2024 What we offer
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. 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. | |
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In your application, please refer to myScience.org and reference JobID 2942408. |
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