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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 22 hours ago
contributes to the concept of a sustainable circular economy. Human activities have disturbed the global nitrogen (N-) cycle, due to a mismatch between the atmospheric N2 fixation and denitrification rates
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accurate flood hazard and risk estimations for present and future cli-mates. The improved model chain consisting of a non-stationary weather generator, a rainfall-runoff model, coupled 1D-2D hydrodynamic
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scientists on, e.g.: Developing self-supervised learning frameworks to extract features from unlabeled high-resolution microscopy data Training and evaluating segmentation models for detecting and
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tunnel testing and statistical modelling using extreme value theory, the project will yield predictive frameworks for structural risk under rare yet damaging wind conditions. The results will support
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research together with cutting-edge materials science and physics. Depending on your background you will work collaboratively on the following tasks with either with a stronger model-development or
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significantly slows down the development of new desirable nanostructures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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batteries at the molecular level. Novel spectroscopic approaches are developed and applied to the characterization of materials under working conditions (operando/transient approach). Relationships between
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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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the change! We offer ideal conditions for you to complete your doctoral degree: Competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling