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Field
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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
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) determine, using 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
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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 define how they interface
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micrometer resolution, allowing validation of the model predictions. Validation and evaluation of the RFBs with optimized hierarchical electrodes. What you bring to the table Very good master´s degree in
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Jülich who are leaders in their respective fields, viz. AI-driven materials property prediction and high-throughput materials development. Computational studies will be performed on Jülich’s world-class
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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that define protein structures, functions, dynamics and interactions Protein structure prediction and modelling, e.g. in Rosetta, MODELLER, AlphaFold, etc. Protein-peptide complex prediction or docking
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. D. positions funded by the ERC (European Research Council) to work on the 'EFT-XYZ' (Effective Field Theories to understand and predict the Nature of the XYZ Exotic Hadrons) project-advanced-ERC-2023
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover