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, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large
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evaluation of prototype implementations. More generally, the PhD thesis is part of a large initiative at Serval and SnT, which aims to support the reliable deployment of machine learning systems by providing
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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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profile A PhD degree in Computer Science or a closely related field A research track record in AI, with openness to interdisciplinary collaborations Expertise in some area of AI such as machine learning
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-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put on discovering biophysical
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driving, in-car monitoring, industrial automation, and security surveillance. The research, called "R4DAR," aims to leverage emerging 4D imaging technology with Massive MIMO to create image-like radar
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of metabolic network modelling linked to epigenetics Carry out machine learning, and integrative analysis of large epigenome datasets Communicate research results in international conferences and journals Work
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and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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essential. Most importantly, the candidate should be curiosity driven and willing to constantly learn new things! Qualification: PhD degree in Computer Science, Informatics, or Software Engineering obtained
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, machine learning, data visualization, digital hermeneutics; an interest in media history or history of technology would be an asset Fluency in English and good knowledge of French or German Ability to work