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design and identifying emerging methodologies. Processing and analyzing large experimental datasets using scientific computing tools (Python/Matlab). Maintaining laboratory instrumentation. Preparing
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detectors and particle accelerators. Applicants should be highly motivated to work in a cross-disciplinary environment on R&D and engineering activities. The full job description is here: https://web.mit.edu
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» Earth scienceYears of Research ExperienceNone Research FieldEnvironmental science » Global changeYears of Research ExperienceNone Additional Information Eligibility criteria http://www.cnrs.fr
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. This role focuses on delivering high-quality, data-driven analysis and insights that inform strategic decisions across the University. You will manage big data, develop evidence-based reporting, and support
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of this position, after meeting the posting requirement of three (3) calendar days. If you have any questions, please visit our Careers site at https://careers.utrgv.edu for detailed contact information. Additional
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 10 hours ago
Experience1 - 4 Additional Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteSwiss Federal Institute for Forest, Snow and
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, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See https://equity.unl.edu/notice
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secure data platforms Large-scale clinical, imaging, EHR, and omics datasets through DAPHI and institutional collaborations A dynamic, interdisciplinary community of data scientists, statisticians
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various data sources, including nationwide registries from Statistics Netherlands and large-scale longitudinal cohort studies, to investigate CHD, MI- and ischemia-related outcomes, intermediates, and risk
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Statistics Netherlands and large-scale longitudinal cohort studies, to investigate IS and ischemia-related outcomes, intermediates, and risk factors. You will enrich these data sources with relevant