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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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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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oral and written English Ability to convincingly convey the importance and impact of a complex scientific project to a broad range of stakeholders Of merit are: Experience in developing custom AI models
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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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written English Ability to convincingly convey the importance and impact of a complex scientific project to a broad range of stakeholders Of merit are: Doctoral degree in data science or another relevant
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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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bioinformatic support to collaborative projects with Genomic Medicine Sweden, as well as researchers working with non-model organisms, additional discipline-specific skills would be valuable. These include
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for HPC systems and the AI factory, establishing repositories of critical reference data sets and models, and leading the development of data labs and similar collaboration spaces. Together with the NAISS
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and written communication skills. Ability to convincingly convey the excitement and impact of a complex scientific project to a wide range of stakeholders. The ability to successfully lead negotiations
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor