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) Documented record of advanced quantitative methods skills in R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches
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R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches Familiarity with large-scale survey data, conflict and
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biology, molecular biology including mammalian cell culture is required Documented knowledge in bioinformatics and programming (Python, R) is required Experience in LC-MS and mass spectrometry is required
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biochemistry are required Profound knowledge in bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications
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project “ComDisp: Community-Centered Modeling of Housing-Related Health Disparities.” ComDisp develops a grassroots modeling framework to predict health disparities under different climate change scenarios
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health disparities under different climate change scenarios. Addressing housing-related health risks in the USA, Vietnam, Turkey, and Ecuador, the project integrates community engagement, data science, and