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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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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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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
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candidate will lead advanced statistical analyses integrating ecological datasets with spatiotemporal modelling frameworks. The work will contribute with evidence-based data to development of ecosystem-based
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, Statistics, computational biology, related disciplines or equivalent. They should be self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese
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to different experimental platforms, desert environments and farmer’s fields at national and international level Qualifications and Experience Essential Ph.D. in Soil Microbiology, Microbial-Plant Interactions
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and advanced statistical methods in studying a variety of issues related to HIV and other health conditions, including but not limited to, community resilience, racial/ethnic disparities of HIV care