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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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assets include strong programming skills, experience with modern machine-learning techniques such as neural simulation-based inference or transformer architectures, and familiarity with fitting methods and
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vehicles. Another research focus is on solid-state pulse modulators for medical applications (computer tomography/cancer treatment) and accelerators (CERN). For the design and optimisation of the various
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machine learning and concurrent programming will be particularly desirable. You should have a PhD in experimental High Energy Physics and have the potential to be a leader in the field. Experience with
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of Research Experience1 - 4 Additional Information Eligibility criteria We are looking for a doctor in particle physics with less than two years of experience after the PhD. Experience in machine learning and
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | about 2 months ago
Position Description The SLAC National Accelerator Laboratory (SLAC) is seeking a Research Associate (RA) to work on Machine Learning (ML) and Artificial Intelligence (AI) for high energy physics
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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in the design and development of the detector upgrade. The LPC is also a major hub for Machine Learning and AI developments for particle physics. There is close and frequent collaboration with
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modern machine-learning techniques, will be exploited to improve the discrimination between the different polarization states. The analysis will use the complete Run 2 and Run 3 datasets collected by
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community, and will work on networking R&D projects in association with Caltech HEP, Fermilab, ESNet, Internet2, the CENIC regional network, CERN and campus network engineers in state of the art network and