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candidate will conduct numerical simulations, develop and implement computational methods to interpret complex data, and contribute to the preparation of grant proposals, progress reports, and peer-reviewed
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Health Sciences. The position will be focused primarily on analyzing data from projects related to emergency medical services, focused on stroke care, and climate change implementation science. This role
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the impacts of heat exposure on non-communicable diseases, including among firefighter populations, leveraging linked health records and environmental exposure data. However, this opportunity is unique in
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available in the Center for the Chemistry of Molecularly Optimized Networks (MONET) at Duke University. The position will support the development and use of data tools for polymer network chemistry, lead and
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computational social science or data science (broadly defined). This individual will help design, execute, and analyze a series of field experiments on a platform created by the Polarization Lab for scientific
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. QUALIFICATIONS: REQUIRED: - Ph.D. or equivalent doctorate in a relevant field, including but not limited to environmental economics, urban economics, finance, public policy, data science, or urban planning
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colleagues across the Duke research community. Required Qualifications: Education/Training- PhD, physics, mathematics, quantum information/mechanics Experience- Preferred--device design, fabrication and
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explores the ecological, historical, and social dimensions of wildfire through classroom and field experiences. The fellow may also lead a Climate+ summer data science project integrating wildfire-risk data
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, Molecular Biology, or a related field Preferred Qualifications: Expertise in experimental design and quantitative data analysis Strong written and verbal communication skills, attention to detail, and ability
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individual will implement, simulate and analyze models of epileptic source localization from EEG signals. Collaborate with clinicians to obtain and analyze imaging, EEG, and outcome data. Prepare results