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must be ready to conduct research involving the design of novel behavioral interventions, conduct human studies, and build computational models to implement existing behavioral paradigms such as Just In
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in statistical network modeling, with applications in health and social science data. The scholar will have an opportunity to collaborate with other researchers, and mentor graduate and undergraduate
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: Prior background in studying bio-molecular condensates using a combination of biochemistry, fluorescence and quantitative modeling methods is highly desired. Prior backgrounds in single-molecule imaging
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molecular biology techniques, 2D and 3D cell culture models (hydrogels), imaging techniques (TEM, SEM, confocal), protein analysis (immunohistochemistry/immunofluorescence), and handling of rodents. Specific
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or disease modeling in R and/or Python statistics data analysis communication (written and verbal) This does not mean you need expertise in these areas but rather that you have some base knowledge upon which
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experimental, modeling, and analytical characterization and analysis tasks to evaluate the utility of various materials exposed to extreme environments. The successful candidate will provide materials synthesis
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) develop and apply statistical genomic methods to analyze multi-omics datasets for understanding complex disease etiology and (2) develop and apply novel statistical models to analyze EHR data
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function. We utilize a variety of approaches including biochemical, proteomic, genomic, genome editing, and mouse modeling to study these questions. Here are representative recent publications from the lab
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IAQ. Designing and conducting energy, IAQ, and economic simulations of novel control systems. Aggregating, synthesizing, and interpreting HVAC system data from field sites. Developing data-driven models
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). Additional experience and training in basic microbiology techniques and preclinical mouse models, including gnotobiotic mice, are desirable but not required. Excellent oral and written communication skills, as