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all, the traditional statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental
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and correlates will differ between younger adults and the elderly, and females compared to males. Methods: The laboratory uses world-class big-data ‘omics’ analysis of blood immune cells, including
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behaviour, social sciences or psychology (e.g. through courses, applications or student projects), with a preference for experience in handling large survey data. Responsibilities and qualifications Urban
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Evaluating the role of Big Data and satellite technologies in understanding livestock impacts on the upland landscape DoS: Dr Mark Whiteside 2nd Supervisor: Dr Katherine Herborn 3rd Supervisor: Dr
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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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, the extensive image information requires great accuracy and is therefore time-consuming. Today, detailed image information is collected from MRI and CT systems on a large scale in various cohort studies, often
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at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining