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research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems for viral agents. Emphasis is placed on determining
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to environmental and agricultural research to develop marker-driven prediction models for precision agriculture. Under the gudiance of the mentor, the participant will engage in environmental and agricultural
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levels at harvest, we aim to develop predictive models, powered by deep neural networks, that can detect early signs of fungal infection and evaluate mitigation strategies such as soil amendments
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ecological modeling. Learning Objectives: Through this fellowship, the successful applicant will gain valuable hands-on experience and develop expertise in laboratory and cold chain research. The participant
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and technology, environmental resiliency, environmental sensing, ecological modeling and forecasting, risk and decision science, environmentally sustainable material, systems biology, climate change
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education and/or experience in one or more of the following: Experience with mathematical and computer modeling & simulation, mechanics, multi-physics numerical simulations, sensor technologies Experience
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-containment BSL-3 and BSL-4 laboratories utilizing a wide range of techniques such as in vitro and in vivo infection models, high throughput spectral flow cytometry, microneutralization, immuno-depletion and
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of infectious diseases Experience in the use of scripting languages (e.g. python, R, bash, perl) Experience in multivariate statistical analyses, including generalized linear mixed models, and/or variants
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the guidance of a mentor, your research will include assessing the biomedical and biological mechanisms of blast injury using in vitro and in vivo models as well as biological samples collected from human