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Field
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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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maps of the distributions of small molecules within the cell. Determining the spatial distribution of small molecules within cells is crucial for understanding fundamental biological mechanisms, but it
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problem formulation from solution concepts, integrating models from different disciplines, operating at different time/spatial scales, analyzing the performance, and cost/schedule/risk aspects of the system
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organoids, CRISPR-Cas9 gene editing, single-cell RNA/ATAC-seq, and spatial transcriptomics. A PhD, MD, MD/PhD, or equivalent degree in biomedical sciences-related fields and a track record of publications in
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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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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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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 | 1 day ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g
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spatial function) and alpha-synuclein (a protein that causes Parkinson’s disease and Dementia with Lewy Bodies) affect brain circuits. The postdoc’s work will encompass studies that are actively collecting
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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