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& Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and opinion dynamics. Our goal is to gain a deeper understanding of
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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is funded from 1 November 2025 to 31 October 2028. Who we are: The Independent Research Group Receptor Biochemistry harnesses the complex interplay between proteases and receptors during plant-pathogen
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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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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glycosylation, the most complex cellular enzymatic process chemical or chemoenzymatic synthesis of glycan-based reporter molecules and small molecule inhibitors contribution to scientific primary publications
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part-time, with 65% of the regular weekly working hours (currently 25.35 hours) and should be used for a doctorate. Participation in the accompanying doctoral programme is compulsory. This serves
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Universität Berlin. The position is part of the research group Quality.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project ‘GluAmin
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on collective dynamical phenomena of complex systems and networks with a focus on strongly externally driven systems; application to fields in physics, engineering and biology, developing a computational toolbox
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complex flow system with a focus on its interaction with wind turbines, providing essential insights to meet the global demand for renewable energy. We employ a multidisciplinary approach that includes free