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project focused on urban biodiversity modelling and spatial ecology in Singapore. Key Responsibilities: The Research Assistant/Associate will contribute to the development of species distribution models
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
tissues and organs as spatially organized metabolic and chemical landscapes using imaging mass spectrometry. The PhD project combines spatial metabolomics, spatial exposomics, and tissue morphology
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
sound knowledge of statistics, machine learning, image analysis, or spatial data analysis The ability to assess algorithms and models not only from a technical perspective, but also in terms
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To make reliable predictions and analyses of air pollution, data assimilation methods, which integrate observational data into model simulation to update the model state and the underlying
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Contribute to the analysis of single-cell RNA-seq, spatial transcriptomics, and multi-omic datasets Apply computational and machine learning approaches to build mechanistic biological models and rationally
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working experiences, and professional mentorship and support. The postdoctoral associate will be affiliated with the Center for Avian Population Studies (CAPS, https://www.birds.cornell.edu/home/center
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analyses and developing habitat maps using marine datasets. Applicants should possess strong analytical skills and experience with spatial modelling and statistical software such as R, Python, or MATLAB
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. Support maintenance of the Duke Forest’s GIS database, including GPS data collection, producing spatially explicit management records, and performing basic cartography and spatial analysis tasks. Assist in
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of unique new datasets using cutting-edge experimental approaches (e.g., long-read spatial transcriptomics) across diverse organs, from the brain to the gonads, with state-of-the-art computational and deep
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., long-read spatial transcriptomics) across diverse organs, from the brain to the gonads, with state-of-the-art computational and deep-learning approaches. Projects may also include detailed molecular and