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communication and enforcement of rules and regulations for all staff members and student workers supervised. Other Requirements or Other Factors: Minimum full time (12 month) position in a large university
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world leader in genomics. The primary mission of the HGSC is actionable translational research across the full spectrum of human health and disease using large-scale genomic data to drive collaborative
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convolutional neural networks (CNNs) and large language models (LLMs) to analyze retinal and corneal data including visual fields, fundus photographs, optical coherence tomography (OCT) images and genetics data
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molecular biology, microbiology, biochemistry techniques in the area of Salmonella biology and pathogenesis. Managing large data sets, synthesizing and integrating different types of data to come to
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of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with their curiosity and their continuous
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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the fundamental understanding of pesticide residues in soils through experimentation, modelling, and big data analysis. You will: Combine existing farm management, soil property and soil pesticide residue data
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implementation of various projects, including (but not limited to) scaling, algorithm development, scaled score development and documentation. Support the creation, management, and retention of large-scale data
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science, information science, data science, (bio)-statistics, (applied
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
Geotechnical Engineering, Civil Engineering, or a related field, and should demonstrate strong expertise in at least two of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian