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atmospheric models on clusters and supercomputers. Experience with code parallelization, MPI (Message Passing Interface), and performance optimization for large-scale simulations using models such as WRF-Chem
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systematically with several stakeholders and parallel activities. The following experience is particularly advantageous: Implementation research and use of established frameworks, particularly PRISM and/or RE-AIM
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different fracture modes interact in layered structures. You have worked with extrinsic toughening mechanisms in laminated composites, including fibre bridging and related processes, and you understand how
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communication skills and motivation to work collaboratively Ability to work independently and manage multiple projects in parallel Proficiency in spoken and written English Desirables: Hands-on experience with
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implementation in FEniCS/FEniCSx/ABAQUS UEL,UMAT. Strong publication record in mechanics, materials, applied mathematics, or related journals. Proficiency with HPC, parallel solvers (PETSc), and version control
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generation, conversion, and utilization in different electro- and thermo-mechanical systems where the study of heat transfer, fluid mechanics, reactive flows, as well as solid mechanics plays a central role
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to the mathematical foundations of entropy, randomness and irreversibility, with possible directions including large deviation theory, algorithmic randomness, ergodic theory, quantum entropy, operator algebras and
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of the project. The Mathematical physics position will contribute to the mathematical foundations of entropy, randomness and irreversibility, with possible directions including large deviation theory, algorithmic
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral Researcher Mission Despite recent technological advances both in the data management
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exploration and optimization of the process parameter space, as well as for adaptive, data-driven machine learning approaches to map the electrolysis process to a digital twin. In parallel, data workflows and