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We have a new and exciting Postdoctoral Research Assistant position available within the CRC-STARS spatial biology team, analysing and interpreting spatial transcriptomic data. You will work on the
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for collecting data on environmental and health parameters (air quality, noise, mobility). GIS Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban
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candidate will contribute to projects involving participants with implanted intracranial electrodes and wearable non-invasive sensors, with a focus on memory consolidation, spatial navigation, and neural
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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Machine Learning Appl Deadline: none (posted 2025/08
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated
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for preprocessing, integration, and modeling of heterogeneous data (spatial, temporal, tabular) -Conduct research in explainable AI and uncertainty quantification applied to agronomic decisions. -Collaborate with
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development. Key Responsibilities: - Develop and implement spatial analyses of environmental exposures - Create and validate neighborhood typologies - Analyze associations between environmental factors and
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of techniques for countering information maneuvers, differences in online harms and influence campaigns across countries, geo-spatial differences in online harms. Successful applicants will need experience in
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temperature. The successful applicant will Analyze imagery from NASA ECOSTRESS instrument on International Space Station for retrieval of surface infrared radiances and sea surface temperature at 70 m spatial
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conduct advanced quantitative (statistical, spatial, etc.) analyses relevant to climate equity, environmental justice, and/or environmental health; translate complex data and analyses for mainstream