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childhood into adulthood. The role involves working with large-scale longitudinal datasets to explore gene–environment interplay and developmental risk pathways. The successful candidate will join a vibrant
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong
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to study the interaction between behavioral goals, life experience, and sensory processing. Our experiments merge a range of approaches, including large-scale multi-area in vivo neural recording, wireless
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skills including the statistical analysis of large data sets. Prior experience in one or more of these techniques: mouse survival surgery, two-photon microscopy and analysis, patch-clamp recording, single
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work on large-scale understanding of coastal wetlands - primarily mangrove forests and tidal marshes. This will include mapping and modelling of distribution, value, condition, and opportunities
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural
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work on large-scale understanding of coastal wetlands - primarily mangrove forests and tidal marshes. This will include mapping and modelling of distribution, value, condition, and opportunities
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will work with existing FH patient cohort data sets from France, Portugal, Czech Republic, and Turkey, which will be expanded with multi-level multi-omics data, including genetic, transcriptomic