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validate the concept. This includes: - Translation of simulation insights into reactor design - Experimental investigation of particle retention and transport - Comparison between model predictions and
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27.02.2026, Academic staff Cancer kills through metastasis, yet we still cannot reliably predict which patients will develop it or trace metastatic disease back to its origin. As part of the BMFTR
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Project This project aims to develop the Amazonian Early Warning System (AmEWS) - a near real time, data- and model-driven platform that focuses on multi-hazard risk prediction for the Amazon rainforest
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of the linear-scaling Wannier optics approach, with the goal of enabling predictive simulations of optical excitations in large and structurally complex systems. Particular emphasis lies on the theoretical
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arise between physical assets and their nominal digital designs, complicating accurate prediction of structural behavior and sustainable lifecycle management. This research aims to overcome
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
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predict food-effector systems. Key Responsibilities • Develop graph-based (multi-)omics analysis algorithms • Benchmark graph-theoretic against graph-ML approaches • Analysis of food-related (multi-)omics
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-based model for monitoring the condition of helicopter components is being developed as part of this project. With the help of flight test data, this model is to be calibrated and used to predict
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, the other one will be hired at the University of Queensland. The rapid advance of smart technologies applied to the agriculture and livestock sectors, for instance, drones, eartags, weather prediction