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research. Interests and/or background in Arctic research, hydrological modeling, surface water fieldwork, community engagement, and/or spatial statistics are also a plus. PROJECTED START DATE There is
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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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understanding of statistics. The ability to analyse DNA-sequencing data is required (exomes, genomes, duplex sequencing); experience analysing RNA-sequencing data (bulk, single cell, spatial), or other -omics
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single-cell and spatial multi-omics datasets. The primary focus of this role is to delve deeper into the molecular mechanisms driving intra-tumor heterogeneity, plasticity, and therapy resistance
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 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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-cell communication analysis and pathway analysis on bulk, single-cell and spatial transcriptomics data Prepare and maintain technical documentation for data and analysis files. Summarize, interpret, and
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to participate in fieldwork. Experience with a range of statistical methods and spatial analysis tools including GIS or a related software (such as Q-GIS). Preferred Qualifications Experience driving small boats
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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