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society are required. Knowledge and skills of GIS and spatial studies are considered advantageous. To apply, please submit your application at https://careers.purdue.edu and include the following materials
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multiparameter immunophenotyping, transcriptomics, proteomics, leukocyte functional assays, and statistical and computational biology to define mechanisms of cellular and humoral immunity to the transplanted organ
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and statistical analyses, and scientific English will be appreciated. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6049-JEAFOL-001/Default.aspx Work Location(s) Number
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on this position will be the development and implementation of novel statistical and computational methods with applications to system biology problems and spatial transcriptomics datasets. The work will involve
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proficiency in integrating spatial data into 3D models using sophisticated interpolation techniques. Additionally, the postdoctoral researcher will contribute to transforming mining liabilities into valuable
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other
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happens in source areas is also essential for interpreting developments in nature reserves. You will be responsible for: statistical evaluation of air-quality monitoring network designs, including
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analyses of public and confidential datasets relevant to the funded projects. Responsibilities include applying causal inference, spatial econometric, and multilevel modeling techniques to examine the
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in the Biodiversity Dynamics and Conservation Group, a team of about 30 persons. Our group studies patterns of biodiversity and biodiversity change at various spatial and temporal scales, with a
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multiparameter immunophenotyping, transcriptomics, proteomics, leukocyte functional assays, and statistical and computational biology to define mechanisms of cellular and humoral immunity to the transplanted organ