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force measurements on actual textile manufacturing machinery in collaboration with leading industrial partners. The goal is to develop a predictive modelling framework that can serve as a digital twin of
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vibratory extraction and jetting, supported by experiments at multiple scales and advanced numerical modelling. By studying ageing effects on extractability and predicting mechanical responses, the project
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optical activity, for strong and predictable enantioselective interactions with nanoscale biological entities, such as proteins and amyloid fibrils. Three-dimensional (3D) investigation of the NPs structure
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applicable methodology to design chiral nanoparticles (NPs) with exceptional optical activity, for strong and predictable enantioselective interactions with nanoscale biological entities, such as proteins and
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the fundamental aspects of transcriptional control, this project also opens new avenues for the design of climate-resilient crops. Supported by single-cell profiling and predictive artificial intelligence models
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training data. You will unravel the cis-regulatory code controlling context-dependent gene expression and use this information to design synthetic promoters. You will train and evaluate predictive models in
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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, and predict their impact on species-specific properties of human neurons. This highly multidisciplinary project will be undertaken in active collaboration with our two labs, at a unique interface of top