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(for example, the distance between the sensors) or based on statistical properties of the measured data (for example, the correlation between the measurements of the different sensors) [2]. Graph-based learning
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of haematopoietic cells are influenced by different microenvironments. To achieve that, we use state-of-the-art single-cell RNA-seq, multiome, and spatial transcriptomics data generation combined with computational
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appear to have greater edaphic specialization in the colder or drier parts of their distribution. Differences in growth potential across species may also be important; for example, greater overall carbon
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The Mathematical Modelling of Infectious Diseases at Institut Pasteur consists of 12-15 researchers at different stages of their career developing state-of-the-art statistical and mathematical methods to analyze
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of renewal subject to satisfactory performance. Applicants should possess a Ph.D. degree in Computer Science, Mathematics, Statistics, computational biology, related disciplines or equivalent. They should be
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 3 hours ago
the statistical agency within the U.S. Department of Energy (DOE). It collects, processes, analyzes, and publishes data to inform the economic activities of the American people and policymaking by DOE
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analyses (duration models, difference-in-differences, causal inference methods) •Drafting and co-authoring scientific articles •Contributing to the organization of interdisciplinary events with the ADMI team
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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us
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its features, it enables joint fits of heterogeneous data sets e.g. from different event types, from differents gamma-ray instruments. Some work have also demonstrated that multi-wavelength (from
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lead advanced statistical analyses integrating ecological datasets with spatiotemporal modelling frameworks. The work will contribute with evidence-based data to development of ecosystem-based