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Field
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of very-high-energy gamma-ray sources, in the context of study of magnetic fields in the Milky Way galaxy and in the intergalactic medium. The work will include development of numerical code for modelling
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— The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according
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Eligibility criteria Numerical analysis and finite element method Solving anisotropic problems Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7340-SOPBAU-024/Default.aspx Work Location
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of quantum error correction, tensor networks, and/or machine learning. Experience with programming and numerical methods is preferred. Overtime Status Exempt: Not eligible for overtime Appointment Type
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, or on the observation and monitoring of science and technology or system of higher education, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20
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to translate rigorous methods into practical tools. QUALIFICATIONS: Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer Science, Industrial Engineering, or a closely related field by start
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel
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-class seminar series. The Center also hosts numerous workshops, conferences, and other academic events that foster collaboration, idea exchange, and visibility, providing an exceptional platform
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following