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methods for image classification including machine learning and deep learning. You will develop clear workflows that allow for regular update of the derived models and maps. Furthermore, you will work
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responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling, or generative modeling. Collaborating with
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Metagenomics, meta-transcriptomics and metabolomics data analysis and familiarity with gut microbiome research. Machine learning for genomics (representation learning, generative models, causal inference). Multi
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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-time behaviour, and mathematical properties of magnetised plasma models (such as magnetized Vlasov–Poisson and Vlasov–Maxwell systems). - The position includes teaching responsibilities, such as
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modelling and AI/ML for the quality monitoring/control, at the end offering to the society novel nanostructured materials, their shape-forming and integration into devices. Your tasks We are seeking a highly
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transduction, cell culture, and immune functional assays; supporting the development of in vivo models, such as adoptive T-cell transfer in mice, for preclinical testing of engineered circuits where relevant