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the following research areas: Engineering – Energy Science & Engineering Engineering – Environmental Science & Engineering Knowledge of numerical modelling of thermochemical conversion processes of biomass and
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-41 https://doi.org/10.1016/j.psep.2020.07.017 🎓 What you will gain • Strong expertise in advanced kinetic modeling • Hands-on experience with calorimetric instrumentation • Exposure to DFT and AI
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command of English. Knowledge in project field. Selection process Please see https://resurseumane.ase.ro/non-gaussian-self-similar-processes-enhanci… Website for additional job details https
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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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Description Are you excited about using large-scale AI to accelerate scientific discovery? Join a Horizon Europe project developing next-generation scientific foundation models that combine knowledge graphs
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biology approaches to simulate biological models at different time-scales in the context oft the development of the PhysiCell/PhysiBoSS modelling systems(Ponce-de-Leon et al., 2023). In particular, we
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Experience with simulation tools (e.g., COMSOL, FEM, MATLAB, or similar software) Knowledge of optimisation methods, data-driven modelling, or control strategies is advantageous Understanding
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related to staff position within a Research Infrastructure? No Offer Description Mission: Model and simulate Langevin equations applied to ion channels. Functions to be developed: Implement stochastic
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 8 days ago
university studies (Master/Diploma) in the field of Physics, Applied Mathematics, Computer Science, Computational Modeling and Simulation or related field # Knowledge of Numerical solution of partial
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Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Postdoctoral Research Associate: Mathematical and Topological Foundations of Knowledge Analysis in the Science of