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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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will have a strong background in research processes, including report writing, and producing high-quality publications, with experience in cardiovascular modelling, fluid–structure interaction or high
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Model. In parallel, the group is engaged in hardware activities related to the development and implementation of new FPGA-based trigger processors, both for the operation of the ATLAS muon spectrometer
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cost allocation; and sector coupling with heat and transport. The work involves system-level modelling of investment and operation to assess how alternative market designs affect the total cost
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at the UMIC in resolving methodological and technical issues. Developing and implementing suitable procedures for scientific data management on the High-Performance Computational Cluster. Participating in
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understanding of thermal-fluid system architecture, including component-level behavior (e.g., heat exchangers, compressors, refrigerant cycles, control valves) and their integration into system-level performance
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written and spoken English and work constructively in an interdisciplinary, international team. Experience with quantum software frameworks, high-performance computing, open-source software development
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electrocatalysis to contribute to the externally funded GETCO2 projects and collaborate with experimental researchers. Your key responsibilities will be to: perform first-principles/DFT studies of electrocatalytic
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data assimilation systems on Unix/Linux and high-performance computing platforms. Evaluate model and assimilation performance using statistical and dynamical diagnostics and verification against
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-solving skills, creativity, and have a demonstrated ability to perform high-quality research, along with excellent oral and written professional communication skills; proven experience in conducting high