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sensitivity analysis, impact of the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy
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-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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of self-assembly for specific types of molecules. Here, we use symmetry and the geometric properties of the molecules in order to calculate bounds that help to predict specific behavior. Moreover, we would
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 3 months ago
models as predictive tools to address questions regarding the response of deep-sea ecosystems to various pressures. A key question addresses the best combination of ML and network analysis to maximize
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. Here, we use symmetry and the geometric properties of the molecules in order to calculate bounds that help to predict specific behavior. Moreover, we would like to more widely explore the possibility
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micrometer resolution, allowing validation of the model predictions. • Validation and evaluation of the RFBs with optimized hierarchical electrodes
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approaches in the powerful model systems zebrafish and fruit fly, and structural biology (including AlphaFold predictions and cryo-EM), we will dissect the roles of these novel mRNA export regulators and
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fields, viz. AI driven materials property prediction and high thoughput materials development. Computational studies will be performed on Jülich`s world-class computational and AI infrastructure. Your
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the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure