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materials. The research focuses on developing advanced models to deepen the understanding of properties, behaviors, and interactions of soft materials, aiming to enable innovations in organic electronics
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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developing complete models. Example applications include models for predicting material structure and properties, neural networks replacing quantum chemistry with knowledge-based approaches, improved materials
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developing complete models. Example applications include microscopy image data, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics data, and
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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: • Designing and conducting multi-omics analyses (including genomics, transcriptomics, proteomics, metabolomics). • Constructing new AI-driven multi-omics models • Supporting occasional teaching and supervision
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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integrity in the design process calls for a technical model of the product concept, i.e., mathematical models of the product and its in-service environment, which inevitably must incorporate the influence