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Health or other related disciplines with at least 2 years of post-bachelor's work experience. Previous work experience in big data analysis, managing large databases of multiple research projects relating
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dynamic and collaborative research environment. Basic data science skills including the statistical analysis of large data sets. Prior experience in one or more of these techniques: design and generation
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
of English (Knowledge of German language not required) Additional experience in optics, machine learning, big data, in-strument design, image analysis, or electronics is a plus. Key responsibilities Design
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of computer simulation models that are open for reuse by health researchers and the NHS. The post holder will conduct cutting edge research that builds on our preliminary research with Open Weight Local Large
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, therefore, has a large international community and a lot to offer to international employees. Because we expect you to work and live in the Netherlands our team of advisors on Dutch immigration procedures
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Location Indianapolis Position Summary Are you passionate about genomics, big data, drug discovery, and AI/machine learning? Interested in advancing cutting-edge multi-omics research to explore genetic and
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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both qualitative and quantitative data and coordinating findings across data sources. The postdoctoral research associate will have opportunities to publish emerging findings from these research studies
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization