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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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large part of the project is dedicated to better integrate automation into multiple facets of cyber-range operation, including the federation of infrastructures to deploy complex scenarios in multiple
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and/or experience in one or several of the following areas: Good understanding of the different ML algorithms and architectures Good knowledge in statistics and stochastic models Knowledge in
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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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postdoctoral researcher, all working on topics related to IP law. The faculty is a vibrant European IP hub with a strong research profile in European IP law, ideally located near multiple European courts
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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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solutions Collaborate with academic teams to support joint/double diploma programs and international teaching initiatives Ensure Moodle is effectively tailored to the needs of multiple university partners and
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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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relying on incomplete CMDBs [Kie23]. Thus, multiple tools are used by experts with strong knowledge and previous experience. The main objective of the project is to automate this human-based cognitive