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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 29 days ago
practice, with a particular emphasis on enhancing access to CIH in at-risk and underrepresented populations. Research trainees will have the opportunity to: 1) receive rigorous training that emphasizes
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, or a related discipline, or be near to completion of your PhD. You will have experience in experimental laboratory research, including data generation and analysis, with strong organisational and record
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for increased joint cross-sectorial analysis of supply chain risks and disturbances. This includes qualitative and quantitative aspects of analyzing governance, risk mitigation (e.g. preparedness stock piling
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Manufacturing Energy Efficiency Research & Analysis (MEERA) Group in
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, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to combine research in Remote Sensing and AI with teaching
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history, the CDSS will provide clinicians with personalized risk profiles for relevant adverse outcomes, including self-harm, method escalation, suicide, premature mortality, as well as discontinuation
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evaluation, policy analysis, spatial analysis, and/or hazard assessment. Track record of scholarly and public outreach via academic publications and presentations in the fields of urban planning, sociology
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with molecular assays (cell cultures, histology, PCR, Gel Electrophoresis, qPCR, etc.). - Experience with data management, statistical analysis (including but not limited to, probit models
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applications of the model in research fields that we already cover (e.g., analysis of ice core data; transport of heat, water, greenhouse gases, radionuclides or air pollutants in the atmosphere; inverse
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pollutants, a combination of advanced observations, innovative instrumentation and data analysis is required. Recent developments in miniature atmospheric instruments, low-cost air quality monitoring