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Field
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involvement and innovation in relation to 1) productivity and spatial distribution of marine fish stocks, their habitats and interactions with other species under future climate conditions and restoration
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software
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, you will focus on that. Your job In this PhD project, you will be part of a large consortium of six PhD candidates and three postdocs. Together, we aim to understand the working of storm surge barriers
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unique three-dimensional maps of neurotransmitter receptor distributions in the human, non-human primate and rodent brain Develop efficient processing pipelines enabling the spatial integration
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EV in vivo tracking studies, spatial transcriptomics, imaging mass-cytometry, micro-CT imaging and experimental fetal lung models to address key questions in lung development and repair. This position
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work with researchers and students involved in spatial hydrology. Publish scientific papers in peer-reviewed journals and deliver presentations and progress reports. Contribute to the supervision
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advanced contextual spatial and temporal modelling approaches. You will work on combining multi-source data such as field observations, laboratory measurements, environmental data, and drone- and satellite
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advanced contextual spatial and temporal modelling approaches. You will work on combining multi-source data such as field observations, laboratory measurements, environmental data, and drone- and satellite
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R for working with the project codebase. Desired qualifications Expertise with spatial, temporal, or spatiotemporal modeling, causal inference, AI/ML/DL, causal ML, explainable ML, AI/ML/DL, and other
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based on two first-of-their-kind NION scanning transmission electron microscopes. In this postdoc position, you will be a member of the Electron Microscopy group and be mentored by scientists at CFN