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environment. Committed to continuous learning and staying updated on industry advancements. Professional certifications in relevant areas will be an added advantage. Candidates with exposure to Big Data and AI
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related field. SCUBA Certified. Experience operating a small boat. One (1) year of full time experience with organizing and analyzing large data sets. Preferred Qualifications: Experience with clams and
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 hour ago
sensing, computer vision or an equivalent field. You have experience in spatial modelling of habitats with machine learning and the use of large extent Earth Observation data. Experience in artificial
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pipelines for large-scale biological datasets. The Research Associate will: Design and implement high-performance workflows integrating GPU programming, deep learning, and large-scale data integration. Apply
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closely with system office and institutional HR leaders to support strategies that strengthen recruitment, retention, and alignment with USG's commitment to a unified, data-driven compensation approach
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from large, well-characterized cohorts. These data are often multi-modal (genetic, epigenetic, transcriptomic, proteomic, glycoproteomic), spanning various brain regions and peripheral tissues, and
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, related mental health and social problems, as well as other significant public health risks—especially HIV/AIDS and other infections among at-risk populations. The IBR Data Manager is responsible for data
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) Location: Big Rapids, MI 49307 Department: College of Engineering Technology Advertised Salary: $12.48- $13.24 Summary of Position: Have you taken welding classes and want to assist underclassmen in
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office staff. Supports benchmarking, assessment, and evaluation of programs/data to guide future planning. Serves as the logistics liaison for large-scale programs hosted by OUR, including
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possibility of partially observed data. The proposed methods are expected to be complemented by efficient computational techniques, enabling their application to real-world datasets, including large-scale ones