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such as artificial intelligence, geographic information systems, and statistical methods. The researcher will be responsible for: Helping collect, organize, and ensure interoperability of clinical
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evolutionary mechanisms: for example, heterozygote advantage (HA), negative-frequency dependent selection (NFDS) or spatially/temporally fluctuating selection (FS). Recently, new research showing that balancing
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inference, bias mitigation, and statistical modelling. Expertise across diverse epidemiologic methods and content areas is welcomed. Develop a research program that incorporates rigorous epidemiologic methods
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geospatial information (land use and cover, biophysical, climate, management practices, etc). • Contribute to the development of spatial and statistical models that describe the interactions between soil and
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inference and prediction of gas dynamics at high spatial and temporal resolution, and in turn more effective climate change mitigation, urban air quality management, and rapid response to hazardous releases
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agricultural science with a quantitative focus (or an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and
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lack reliable uncertainty quantification. The methods developed in the project will tackle these shortcomings, enabling computationally efficient inference and prediction of gas dynamics at high spatial
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and Campus Crime Statistics Act, the Annual Security Report (ASR) is also now available for viewing at https://www.sjsu.edu/clery/docs/SJSU-Annual-Security-Report.pdf . The ASR contains the current
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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging
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is an award winning, multi-sectoral team of researchers, technicians and project specialists working on producing data on population distributions and characteristics at high spatial resolution. We