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: Numerical modelling, Geotechnics, Finite Element Method (FEM), Research and development projects, Scientific achievements DESCRIPTION (subject-matter, expectations, remarks): Requirements for Candidate: PhD
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Nantes, Pays de la Loire | France | 15 days ago
conducted within the Ecology and Modelling for Fisheries (EMH) laboratory of the HALGO unit, part of the DECOD Joint Research Unit. Members of the laboratory develop knowledge and methods supporting
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at the Physics & Astronomy Department of the University of Bologna (Italy) are invited, for a research project with title : “A numerical survey of the magnetisation of the cosmic web by feedback mechanisms
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Context Statement Position Overview A postdoctoral position is available in the Department of Physics at the University of Idaho. The primary focus of this position is advancing numerical relativity methods
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(SAF), specifically investigating the local and global extinction of bluff-body swirl spray flames. In this role, you will utilise laser diagnostics and numerical tools to characterise combustion species
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Geography, and the like Demonstrated analytical, programming, or numerical methods skills (e.g., C++, Fortran, Python, R, Matlab). The candidate must be fluent in written and spoken English and Portuguese
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, version control) and numerical workflows. Experience programming for data analysis and model workflows (e.g., Python, MATLAB; FORTRAN/C familiarity for model configuration). Demonstrated verbal and written
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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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; Giauque et al., 2023). The PhD work is structured around the following key milestones: 1. Implementation and validation of real-gas model: Develop, verify and validate real gas equations of state capable
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numerical modeling (ocean, sea ice, atmosphere) or in physical model emulation; Knowledge of data assimilation methods (4DVar, EnKF, En4DVar) and their practical implementation; Research experience in machine