50 molecular-modeling-or-molecular-dynamic-simulation Fellowship positions at University of British Columbia in Canada
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, nursing, psychology, sociology, anthropology, education) Experience conducting multivariable modeling research, large-scale population survey data preferred Experience with SPSS required, comfortable using
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. The research plan of each Fellowship must address scientific questions within the scope of AGS disciplines. These disciplines include Atmospheric Chemistry (ATC), Climate and Large-Scale Dynamics (CLD
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, spatial modeling, and/or remote sensing is desirable. Proficiency in GIS, R, and/or Python for data analysis, modeling, and spatial analysis is also desirable Excellent written and verbal communication
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embrace the complexity of digital health implementation and data-driven predictive modelling in low-resource settings with passion, resilience, and lots of creativity. Find yourself in new areas of inquiry
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algorithms Significant experience and publication on AI and image processing Experience with foundation models, explainable AI and/or efforts to translate AI to routine use are emphasized Highly motivated with
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significant research experience and deep familiarity with AI algorithms Significant experience and publication on AI and image processing Experience with foundation models, explainable AI and/or efforts
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the importance of extramural investments in climate science spanning observations, analysis, modeling, and the integration of social, behavioral, and economic research across NOAA mission areas (NOAA Strategic
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Studies, should the application be selected to be nominated to the national competition. Must be completed and accompanied by a copy of the unofficial transcript(s) from applicant university (ies) All parts
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evaluation. We are looking for an individual with a desire to embrace the complexity of digital health implementation and data-driven predictive modelling in low-resource settings with passion, resilience, and
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Africa, with rigorous evaluation. We are looking for trainees with a desire to embrace the complexity of digital health implementation and data-driven predictive modelling in low-resource settings with