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and expanding the group’s project portfolio. Working effectively in multi-partner research projects. Engaging with industry partners in ongoing projects. Supervising students at the M.Sc. and Ph.D
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Destination Earth Climate Change Adaptation Digital Twin Project, Phase 3 (https://destine.ecmwf.int /), where INAR is a contributing member. The Climate DT project is setting up an operational simulation
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using external stimuli. The project is funded by The Royal Society. Find out more about the research and group at: https://langtonrg.web.ox.ac.uk About you Applicants must hold a PhD in in synthetic
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global kilometer-scale climate models (IFS-NEMO, IFS-FESOM, and ICON) in a unified operational workflow producing both multi-decadal climate projections and storyline simulations. Within Climate DT
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? Join our team to develop next-generation multi-aperture ultrasound technology combining distributed sensing, adaptive acquisition, image reconstruction, and AI-driven imaging for groundbreaking clinical
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towards deep, large-scale analyses of STM evolution and action. The focus will lie on a range of arthropods, molluscs, and chordates, with the aim to uncover universal STM design principles as
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computational efficiency of large-scale simulations. The Chair of Computational Methods in Civil and Environmental Engineering at the Technical University of Munich (TUM) invites applications for Doctoral
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process intensification, sustainability, and advanced process control, aiming to develop AI-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex
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place in countries of the Global South and North, as well as the processes of protection, transmission and sharing. Its analysis, conducted across various temporal and spatial scales, prioritises
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systems, gas networks, or coupled multi-energy systems Proficient in programming, especially in Python; experience with C/C++ is an advantage Interest in scientific software development, large-scale