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within the LIENSs Laboratory a 1-year postdoc or a research engineer to improve the numerical modelling of nature-based solutions in coral reef and saltmarsh environments using the numerical modelling
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” in the Moonshot R&D project (Goal 8) https://www.jst.go.jp/moonshot/program/goal8/84_kotsuki.html [Work content and job description] The selected person will address numerical modeling of heavy
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early-career researcher in applied mathematics, physics, or engineering, with expertise in fluid mechanics1, non-Newtonian fluids, numerical methods, and scientific computing2. Background or strong
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(Numerical Analysis and Applied Mathematics) develops numerical algorithms and software for large-scale problems in science and engineering. Its research ranges from algorithm design and analysis to software
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(Abaqus) via user subroutines and conduct numerical case studies to demonstrate the model capabilities. You will have the opportunity to be involved in undergraduate and graduate supervision and teaching
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financial models for capturing complex market dynamics . Assets, principal investigator Prof. Dr. Ciprian Andrei Tudor. The position is limited until 30/06/2026. Applicants with a solid practical experience
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component based on the systemic study of stochastic models with Hermite random perturbation and also with a significant practical part, related to the effective computation of the data and numerical
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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, numerical simulators with coupled physics (flow/reactive/geo-mechanics/thermal) have been developed and often applied to predict the long-term fate of the injected carbon dioxide to ensure its secure
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning