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of different faiths and beliefs. Grounded in the Christian view of human life, the KU aims to create an academic and educational culture of responsibility. The research group Reliable Machine Learning at the KU
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sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR as well as small-scale EMI measurements with root and shoot observations in controlled experiments
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using electromagnetic induction (EMI), and ground penetrating radar (GPR) will be combined with soil sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR
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. It is not feasible to scan the full volume of such samples at the highest desired resolution. Therefore, we require an imaging scheme that acquires relevant features at different length scales and
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 3 months ago
functions to detect ecosystem change and predict ecosystem characteristics under different impact scenarios. The integrated analysis of marine microbial eDNA data and contextual environmental information with
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
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optimization to find the optimal set of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e.g
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. This is because experimental techniques to solve structures of protein complexes favor more stable interactions with larger interfaces and because we lack efficient algorithms to compute similarity between
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of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations