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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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the diversity of aspartic proteases from the model plant Arabidopsis thaliana and deploy chemical synthesis, advanced modelling, protease biochemistry, mass spectrometry and structural analysis methods. A
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these determinants, we will harness the diversity of aspartic proteases from the model plant Arabidopsis thaliana and deploy chemical synthesis, advanced modelling, protease biochemistry, mass spectrometry and
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. Correlated experimental, ab initio and multi-scale techniques are central to our mission: Development and application of advanced simulation techniques to explore and identify the fundamental structures and
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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of Chemistry (Inorganic Chemistry). Our group investigates fundamental questions in bioinorganic chemistry using advanced spectroscopic techniques to understand the structure and reactivity of complex metal
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of Chemistry (Inorganic Chemistry). Our group investigates fundamental questions in bioinorganic chemistry using advanced spectroscopic techniques to understand the structure and reactivity of complex metal
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architectures, capable of capturing the structure of complex, high-resolution NMR spectra – analogous to how language models such as ChatGPT learn the structure of human language. One of the primary goals is to
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the technical and social challenges of Advanced Air Mobility (AAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in
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social challenges of Advanced Air Mobility (AAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly