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diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry
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technologies, such as ontologies and semantic web standards, as well as graph data and knowledge graphs, and circular economy and DPPs is preferential. Documented experience of writing and publishing research
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embedding graph-based problems, particularly those known to be challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits
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queries within embedded knowledge graphs. It will involve designing or adapting efficient indexing structures tailored for vector databases and exploring hybrid neurosymbolic techniques to enhance query
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graphs for heterogeneous pavement engineering knowledge aiming to speed up the learning cycle and support innovation and asset management. Job description The increasing accessibility of data in
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Apply and develop advanced multimodal data tools and knowledge graphs for heterogeneous pavement engineering knowledge aiming to speed up the learning cycle and support innovation and asset
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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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. Your work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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interaction and/or web programming, and human-computer interaction is required. Experience and/or knowledge of semantic web technologies, such as ontologies and semantic web standards, as well as graph data and