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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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Are you fascinated by the chemistry of the gut microbiome? Are you intrigued to learn more about how the bacterial metabolic function is involved and could be targeted in the context of immune
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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at the Chemical Institute in Ljubljana is advertising job vacancies in the field of developing new approaches to synthetic biology for potential therapeutic use. The aim is to design innovative strategies
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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for advancing healthcare innovation. By enabling high-throughput synthesis, precise control over nanoparticle properties, and scalable manufacturing, automation accelerates the development of novel nanomedicines
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. Partnering with Toyota and Demcon TSST, SMIP will showcase this innovation through a self-learning chip prototype, improving performance and durability in automotive applications. Specifically, this PhD
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study designs to investigate how such multi-team systems adapt to unexpected events. Thereby we specifically focus on the role of faultlines--the imaginary dividing lines that split up a system into
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approaches that combine artificial intelligence, machine learning, natural language processing, and social sciences. This collaborative and cross-sectoral approach aims to produce robust methods for evaluating