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expand and improve an existing modelling framework to predict direct and indirect nitrous oxide and methane emissions from agriculture. You contribute to the following activities: Performing a SWOT
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models and monitoring data to assess its current structural state and predict its remaining lifetime. This will enable the condition of welded structures to be monitored throughout their service life
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, link ecological and EO data, and integrate your findings into models to predict ecosystem functioning in response to global changes and management interventions. You will learn how to publish your
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group working on nuclear fuel performance, uncertainty quantification and advanced computational methods for nuclear engineering applications. The group combines physics-based fuel-performance codes with
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of faithfully reproducing the city behaviour through the use of advanced modelling, data science, and AI techniques. One of the key foreseen applications of Urban Digital Twins is to predict the evolution
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to understand and predict biologic effects of particle radiation based on underlying physics, biology and physiology. Within the framework of the research project PIANOFORTE-PRESTO (PRoton therapy Enhancement by
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complex systems, will you help us develop a new generation of road traffic prediction methods? Job description Road traffic is a highly complex dynamic system. Minor disruptions can lead to major delays
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also include generative or predictive modeling of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access
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for analysing authentic, synthetic, and manipulated images or videos. The work will combine predictive performance with explainability, uncertainty estimation, robustness, and generalization. Attention will be
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for individual careers are uneven and hard to predict. Employees face open questions about which parts of their work will remain theirs and whether they can realistically acquire the skills that will matter next