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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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? As part of this learning experience, you and your mentor will be involved in two to four research projects: one involving the efficacy of a hypoxia inducible factor prolyl hydroxylase inhibitor
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promoters. Digital Phenotyping: Application of hyperspectral imaging and advanced imaging tools to detect disease traits beyond the visible spectrum. AI-Driven Data Analysis: Leveraging machine learning
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USDA-ARS Postdoctoral Research Opportunity: Development of Novel Vaccines for Poultry Viral Diseases
of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: The ORISE participant will be part of the research team learning about developing
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USDA-ARS Postdoctoral Research Opportunity: Development of Novel Vaccines for Poultry Viral Diseases
of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: The ORISE participant will be part of the research team learning about developing
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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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team. Anticipated learning objectives for this opportunity include, but are not limited to: Understanding Material Development: Gain knowledge of the principles and processes involved in the synthesis
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online databases or interactive websites. Learning Objectives: TUnder the guidance of a mentor, the participant will learn techniques in genomic epidemiology and machine learning to quantify drivers of IAV
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advance the care for Service members with amputation Collecting and processing human motion capture data Gaining experience on multiple projects involving lower limb amputation Learning about grant proposal
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tolerance for varietal selection. Learning Objectives: Participant will gain laboratory, field, and programming skills to develop the digital twin and other AI models using ground and above-ground sensors and