11 postdoctoral-soil-structure-interaction-fem-dynamics PhD positions at Linköping University in Sweden
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, computational fluid dynamics, and uncertainty quantification with diverse applications. Learn more: Department of Mathematics and Work at the Department of Mathematics . Furthermore, our group maintains active
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foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic communications see our review paper entitled “Semantic
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components to execute complex reasoning and decision-making tasks. These agents are increasingly deployed in domains such as healthcare, finance, cybersecurity, and autonomous vehicles, where they interact
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design with advanced structural, spectroscopic, and electrochemical characterization methods to unravel how ions, charges, and molecular interactions govern doping efficiency and stability. By exploring
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essential, as the position involves interaction with healthcare professionals, patients, and research participants, and requires interpreting medical documents in Swedish. Requirements: Extensive experience
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weather forecasting to cardiovascular medicine. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning
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. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning - constitute fundamental scientific domains that act as
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are conducted within the units Traffic Systems, Quantitative Logistics, Flight logistics, Rail and Public Transport, Mobile Telecommunications, Construction Logistics and Construction Technology. The research is
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technology or construction engineering or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses. Alternatively, you have gained essentially corresponding knowledge
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is