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/RDF knowledge graphs, SPARQL endpoints, and open benchmarking suites to guarantee FAIR, reusable research data Mine and link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: The PhD project is methodologically independent, with
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Engineering, or related fields. Solid background in structural dynamics, wind engineering, and finite element modelling. Experience in programming (MATLAB/Python) and/or structural analysis software (e.g
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cascading hazards. The doctoral candidate will design, implement, and validate a real-time structural monitoringand damage visualization system by coupling IoT-enabled dynamic sensors with digital building
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network of passionate young scientists in Munich. WHAT DO WE OFFER? A structured PhD program created by Munich-based Max Planck Institutes and Universities with English as the main language Individual
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21 Aug 2025 Job Information Organisation/Company GFZ Helmholtz Centre for Geosciences Research Field Environmental science Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 1 month ago
The Department of Process Systems Engineering (Director: Prof. Dr.-Ing. Kai Sundmacher) at the Max Planck Institute for Dynamics of Complex Technical Systems is inviting applications for the PhD
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link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and other multimodal datasets from simulation and experiment Develop benchmarking protocols and toolkits to evaluate AI models
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Your Job: The PhD project is methodologically independent, with the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will
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at demonstrating how teacher learning can be made robust in an event-based framework, that is, when both the teacher model and the learning rules are event- based. The combination of excitable teacher dynamics and