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Field
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
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using mouse models for neurodevelopmental disorders and brain inflammation. Run spatial omics approach including multiplexed protein imaging and transcriptomics. Collect and analyze data from genome-wide
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single-cell and spatial transcriptomics, whole-genome sequencing, high-throughput screening, CRISPR-based functional screening, and patient-derived organoid models. You will work closely with in-house
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% FTE) postdoctoral scholar with expertise in fire modeling and remotely sensed data to support innovative research. This project will improve our understanding of the conditions under which fuel
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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. You will incorporate field survey data, remote sensing and other auxiliary data into spatial modelling processes using techniques such as species distribution modelling and artificial intelligence
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The researcher will be in charge of the implementation of geophysical approaches at the Guyaflux site, Paracou, French Guiana, to spatially extrapolate punctual information on soil obtained from conventional
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and Radiative Transfer models already developed as part of the ANR AGN_MELBa work. This might require running and adapting these models. Then, at a different spatial scale, the multi scale tools will be
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collaboration with modelling (WP3) and societal uptake (WP5) partners; · Development of standardized indicators for evaluating technical, ecological, and societal outcomes. This WP involves close
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mouse models. Utilize advanced technologies such as CRISPR/Cas9 gene editing, single-cell RNA- and ATAC- sequencing, single-cell spatial transcriptomics, and multiplex fluorescence imaging. Collaborate