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relevant innovation. Information Protein tumor markers (TMs) in blood offer a promising, minimally invasive approach to support clinical decision-making in lung cancer. However, their broad clinical
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large pan-European research initiative that brings together researchers, clinicians, and patient communities. Your project focuses on analyzing multi-omics sequencing data from thousands of patients with
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microscopy methods such as light-sheet fluorescence microscopy (LFSM) and the experience in computational data science to handle the resulting large 3D datasets. We are looking for an enthusiastic and creative
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approaches that integrate both qualitative and quantitative research (e.g., combining big data or machine learning with in-depth fieldwork) can also be pursued. Method selection and mastery are viewed as part
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of data structures, static analyses and compiler optimizations, parallelism and concurrency) to turn these new theoretical developments into performant implementations; building state-of-the-art
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data collection fieldwork (quantitative and qualitative) related to health and WASH services followed by econometric and spatial analysis, and engaging with local communities and decision-makers. Your
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Are you interested in cutting-edge research at the intersection of large language models, deep learning, and information retrieval? The Information Retrieval Lab (IRLab) at the University
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degree in Computer Science, Artificial Intelligence, Data Science, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong
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The PhD position is part the prestigious POLARIS (Pathway towards Opportunities for Large scale Applications of Radically Integrated Systems) project. Polaris is a large flagship program (funded by
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at the interface is known. These results will provide essential information for anaerobic process design in recycled cardboard industry under water-saving scenarios. This PhD project comprises the following