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features from unlabeled high-resolution microscopy data Training and evaluating segmentation models for detecting and characterizing defects such as dislocations Applying generative models (e.g., GANs
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participate in the courses, for example by holding lectures during seminars or participating in doctoral study groups. Students' performance in the courses will be evaluated and documented during the programme
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, feed and chemical safety and consumer health protection in Germany on the basis of internationally recognised scientific evaluation criteria. It advises the Federal Government and other institutions and
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. The aim is to evaluate and improve the long-term reliability of these materials for green hydrogen production. To achieve this, your responsibilities will include: Design and execution of experiments
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
evaluation methods Interactive systems for exploring complex networks Candidates interested in theoretical computer science will have the opportunity to work on topics such as graph algorithms, computational
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or for multiobjective optimization problems. Implement the developed algorithms (e.g., in Python) and evaluate their practical performance on artificial and/or real-world data. Teach tutorials (in English) for
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reliability of hydrological models through an innovative end-to-end modelling framework. Specifically, we aim to develop and evaluate a novel hybrid model that combines Transformers with Neural ODEs
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framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement of risk-to-resilience
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well as data processing meth-ods for analyzing block-like structures made of limestone and granite, Evaluation of data using acoustical imaging techniques and passive seismic monitoring, Carrying out
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framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement of risk-to-resilience