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, development, and execution of computer simulations of system related to different replication stages of the HIV virus. Preference will be given to applications with expertise in 1) protein dynamics; 2
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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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Spaces Sciences at the University of Washington seeks a Postdoctoral Scholar to work on numerical simulations and data analysis to inform the search for life on exoplanets. The position will be supervised
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through both academic and non-academic channels The project is multidisciplinary and in the project you will join a large team of researchers from different universities and disciplines. For this reason it
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is looking for a post doc with a background in seafood science and/or seafood development or processing for a large project in collaboration with Food and Agriculture Organisation (FAO), which is an
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 3 days ago
candidate has excellent quantitative and data analysis skills, a proven ability to work independently, and a collaborative mindset. They will be expected to lead their own research projects, contribute
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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allocation policies and task division policies can be designed to flexibly allocate teachers with different profiles to learning activities? c) what sharing mechanisms can be designed to enable cooperation
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity