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Field
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) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including the application of machine learning (ML) methods or large
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semantic querying and reasoning over materials-science/physics corpora Developing pipelines for semantic enrichment of unstructured data, including entity recognition, relation extraction, and automatic
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Genetic Improvement of Dairy Cow Longevity, Using Large-Scale Body Weight Data from an AI-Camera System (Long Live the Dairy Cow) Applicants are invited for a PhD fellowship/scholarship at Graduate
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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PhD Scholarship in Big Data and Analytics for Crop Genetics Modern agriculture and biomedical research are driven by the availability of big data and the development of data science. The recent
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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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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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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analyses using your own data and large public data resources and integrate your findings with clinical data (symptoms, EEG, etc). Finally, you will contribute to other activities of the STXBP1 team