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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical
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application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial peptides Perform and support experimental studies across the METAMIC project
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buildings, smart street lighting, smart factories, healthcare, and robotics. The emerging radar sensors in use by the group employ multiple-input multiple-output (MIMO) technology and can be connected
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the current age lies in joining forces from multiple disciplines to focus on understanding causal and mechanistic links between the microbiome and chronic diseases alongside generalisable pathogenic effects
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an outstanding and dynamic environment for PhD candidates, with multiple seminars, working groups, colloquia, and a doctoral school, which also gives access to multiple training opportunities, including courses
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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in a structured doctoral training environment. The need of microbiome research in the current age lies in joining forces from multiple disciplines to focus on understanding causal and mechanistic links
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use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group