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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 1 hour ago
profile # Ph.D. in the field of Physics, Chemistry, Computer Sciences or Applied Mathematics or related field # Background in mathematical surrogate modeling and machine learning # Experience or familiarity
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of the project. Non-Gaussian self-similar processes : Enhancing mathematical tools and financial models for capturing complex market dynamics - presentation The proposal concerns a particular class of
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Code010374StreetPiata Roamana no 6Geofield Contact State/Province Bucharest City Bucharest Website https://resurseumane.ase.ro/non-gaussian-self-similar-processes-enhancing-mathematical-tools-and-financial-models
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded doctoral position in mathematical and computational modelling
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 6 days ago
, and innovation centre active in the fields of High-Performance Computing (HPC), Data Analytics (HPDA), Quantum Computing (QC), Artificial Intelligence (AI) and their applications. For more, see https
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Fraunhofer-Chalmers Centre (FCC) is a leading research centre in industrial mathematics, modelling, simulation, optimisation, and data analytics. We operate at the interface between academic research and
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topics in international macroeconomics and finance Responsibilities • Conduct empirical analysis • Review and summarize academic literature • Assistant in theoretical and computational modeling • Prepare
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related discipline. A passion for experimental work and capability to develop/apply mathematical modelling techniques will be particularly important for this project. Where to apply Website https
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research in Artificial Intelligence and its ethical, frugal, and sustainable dimensions? Do you have a PhD and a solid experience in research or R&D in AI, with a specific interest in designing models
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The