119 development-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions at Zintellect
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, logistical planning for field and lab research, data collection, statistical analyses, and summarizing results for technical reports. Learn how to conduct both basic and applied research and develop expertise
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traits associated with tolerance to adverse growing conditions. Develop an understanding of how physiological mechanisms are connected to observable plant stress-response traits. Gain exposure to plant
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technical assistance, training, and tools. We help develop and share health communication messages and products that are understandable, accessible, and actionable across various audiences such as the general
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Wyndmoor, PA investigates issues related to the utilization of milk, and dairy manufacturing by-products for the development of novel food, bioactive and packaging ingredients. The Unit is seeking a
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agencies, to identify environmental public health issues and develop appropriate, science-based recommendations. Environmental health experience with issues involving hazardous substances and exposure
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propagating and maintaining diverse plant species; conducting greenhouse inoculation experiments; evaluating symptom development; collecting plant tissue samples; and applying serological and molecular
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approaches to study genes involved in crop trait regulation. Develop skills in analyzing gene function and biochemical pathways associated with plant growth, biomass composition, and crop improvement. Learn
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and related public health outcomes. Develop skills in longitudinal and trend analyses of survival, mortality, and disease burden. Contribute to research aimed at improving understanding of population
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diverse turfgrass germplasm, you will learn methods for evaluating adaptation, color, quality traits, and environmental stress tolerance that support the development of improved turfgrass cultivars. You
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. Additionally, we intend to measure root water uptake using sap flow meters. The data will be integrated using recently developed physics-informed neural networks in order to translate apparent resistivity data