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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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the teams to support the researchers and PhD students. H/She will analyze various sources of data and train AI algorithms, such as voice recordings to identify digital vocal biomarkers, or clustering methods
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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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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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research networks Demonstrated capacity to plan, coordinate, and deliver research projects, possibly involving multiple partners Teaching and Supervision Proven ability to contribute to curriculum design
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represented in our workforce Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions Gender-friendly environment with multiple actions to attract
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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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transitions, with demonstrated ability to develop novel circularity indicators and assessment tools that capture multiple dimensions of circularity including material flows, value retention, and system
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people to fulfil their personal and professional ambitions Gender-friendly environment with multiple actions to attract, develop and retain women in science 32 days’ paid annual leave, 11 public holidays