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candidate, you will: · You must have experience with flow cytometry, molecular biology techniques, cell culture, microscopy, tissue processing, immunohistochemistry, immunofluorescence, data analysis
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• Develop new computational research projects on contemporary antisemitism • Build computational pipelines for social media data collection and analysis • Supervise graduate and undergraduate research
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, evidence synthesis, and quantitative data analysis, enabling the development of targeted and exploratory indicators for monitoring tobacco exposure and chronic disease trends at the population level. You
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bioinformatics and biomarker research. This position focuses on the integration and analysis of complex biological data to identify and validate kidney disease biomarkers. Research Focus Our program leverages
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and non-compliance, analysis of heterogeneous effects and interference; Designing lab experiments, field experiments, and/or surveys; Programming/scripting knowledge suitable for processing raw data
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 15 hours ago
Biology, Immunology, Virology) Candidates will be evaluated on: proficiency in experimental design and execution, time management, data compilation and analysis, data management, and scientific writing
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Details Title Postdoctoral Fellow in Residual Stress Analysis of Ceramics and Glasses School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Materials Science and
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design, corpus or discourse analysis, and statistical techniques of data analysis. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential
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-driven research. Lead and support multi-omics data analysis, including microbiome (16S, metagenomics, metatranscriptomics), bulk and single-cell/spatial transcriptomics, proteomics, metabolomics, and
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analysis, data simulation and imputation. B) Participate in development and testing statistical methods for admixed human datasets. C) Omics (genome, transcriptome, microbiome, epigenome) data integration