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examines how the occupational risks faced by inhabitants of the Roman Empire influenced their choice of preferred cults. The main methods used in the project include spatial analysis, predictive modelling
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for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5126-EMIBAS-021/Default.aspx Work Location(s) Number of offers available1Company/InstituteCentre d'études spatiales de la
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) (Dr. Simpson’s webpage). The original call for the solicitation can be found here: https://www.energy.ca.gov/solicitations/2025-02/gfo-24-307-advancing-designs-and-analysis-high-voltage-direct-current
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workflows. Qualifications PhD in Computational Biology, Genomics, Biomedical Engineering, Neurosciences, or related fields. Proven expertise in single-cell or spatial transcriptomic/proteomic data analysis
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Internal Number: JR91931 Scheduled Hours Empty heading 40 Position Summary Empty heading Performs data management and/or data analysis for investigators using statistical packages. Assists investigators in
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) government, industry, and local NGO’s. Your main contribution will be the development of a spatially explicit agent-based model of the society of the Metropolitan Region of Amsterdam, simulating circular
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in
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-bathymetric surveys from diverse national and global data sources; Analysis of local, regional and global wave data; Determination of theoretical depth of closure and its temporal and spatial variability
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the Laboratory of Geo-information Science and Remote Sensing is an interdisciplinary research group focused on integrated approaches to geospatial systems analysis. Our work applies a complex adaptive systems
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skills. Additional Merits Experience in one or more of the following areas will be considered a strong advantage: Single cell and spatial multi-omics analysis Complex Cellular Systems/ Organoid models