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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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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff. General information: Contract Type: Fixed Term Contract 36 Month Work Hours: Full Time 40.0 Hours per
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mechanistic studies of microbiome-mediated pathogenesis. This is achieved by bridging microbiology and big data analytics in a structured doctoral training environment. The need of microbiome research in
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the advancements brought by AI, there is currently no tool sufficiently intelligent to fully aggregate and utilize diverse data sources to create a comprehensive and adaptive dashboard for taking
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chemical biology help us address these interactions in health and disease? What molecular mechanisms drive neuroinflammation and axonal damage in multiple sclerosis? For more information, please visit our
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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(cumulative; i.e. based on peer-reviewed publications) Conduct an in-depth literature review to support the research plan Coordinate the organization of data-sets, including video data collection and management
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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. The project will involve significant collaboration, sample exchange, semiconductor and device characterisation. For more information on the position please contact Prof. Phil Dale phillip.dale@uni.lu or Prof