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collaborative research projects, demonstrating the ability to work effectively within research teams. Basic understanding of digital twins, encompassing their concepts, applications, and relevance in modern
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these materials at the end of their life is a growing challenge. Current recycling methods often damage the fibres, use a lot of energy, or have negative environmental effects. This project aims
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on the microscopic level translates into the function on a macroscopic level. Imaging biomolecules, together with trace elements, is vital in understanding complex processes, disease mechanisms, or the effects
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the case, then the problem is further complicated by the fact that no single mapping is optimal for all combinations of matrix sizes. As a consequence, any code generated (at compile-time) to evaluate
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no later than the deadline for application. Please note that printed publications will not be returned. They will be archived at Linköping University. In the event of a discrepancy between the English
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at least one of the areas of data privacy, machine learning is required. A successful candidate is expected to have a scientific and result-oriented approach to your work. A very good command of
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with modern machine learning and AI technologies to effectively address large-scale problems. About the research project We are seeking a highly motivated Postdoc to join our group in developing
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are two important stress factors that have gained attention lately, however, their combined effects remain poorly understood. In this project, the postdoctoral fellow will quantify the biophysical stress
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have been ongoing since 2017 to monitor the effects of decreased water inputs to the system. In addition, the project has maintained a nearby long-term monitoring site in a pristine TMCF forest since
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software engineering, Investigating and prototyping future use cases of GenAI agents, Developing and evaluating human-in-the-loop workflows for GenAI-supported development, Analyzing the effectiveness