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computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and
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particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required skills : We
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cytometry Perform genomic data analyses from next generation sequencing data (eg. RNAseq, scRNAseq, spatial ‘omics profiling)—prior experience with genomic data analysis is helpful but not required Stay
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
for high-resolution (e.g. gigapixel) imaging, or high-dimensional statistical approaches for analyzing spatial transcriptomic data. This role involves close collaboration with an interdisciplinary team
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excellent written and oral communication skills. Commitment to working successfully with a diverse student population. Specialized or moderate skills in spatial statistics, data analytics, pixel and object
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–biodiversity relationships are linked to acoustic comfort–restoration outcomes. The models will integrate spatially-explicit structural complexity variables, landscape imperviousness variables, biodiversity
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community at Stanford looking at the health impacts of environmental changes. The successful candidate will have strong data skills, including experience handling complex data structures, working with spatial
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outstanding resource to apply biomedical statistical tools for data analysis for our groups' ongoing preclinical work and tissue assays. Perform RNA sequencing, including bulk sequencing, single-cell sequencing
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disease, and identify causal genes and variants using xQTL analysis and integrating our data sets from hundreds of brains (sn-RNAseq, sn-ATAC-seq, sn-long-read PacBio RNAseq, high-resolution spatial
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on available and harmonized biodiversity and environmental data. The project provides access to a wide range of spatial and temporal biodiversity and environmental data and a fantastic opportunity to become part