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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA
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omics to advance biological and clinical discoveries and develop next-generation theragnostics. The postdoctoral fellows will mainly focus on (1) creating novel computational algorithms to analyze and
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tools to interpret, analyze, and visualize multivariate relationships in data. Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data
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project was to develop a novel, algorithmic tool that allows it to compare survey information from across countries and years. Using the tool, the team has created a comprehensive database of Afrobarometer
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into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking
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single-cell sequencing, spatial transcriptomics, and machine learning algorithms to to understand, at the tissue and organ level, how specific cellular communications—from synaptic connectivity to neural
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Familiarity with machine learning/algorithms/computational methods such as sparse methods for regression such as lasso, elastic net, random forests; logistical and Cox regression; longitudinal (time series
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statistical techniques on available data. Drive collection of new data and the refinement of existing data sources; apply and use algorithms or other advanced techniques to accomplish this. Explore data from
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biostatistics, operation research, epidemiology (with strong computation skills), or related fields and hands-on experience in algorithmic implementation and statistical programming. Strong programming skills in