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. This fellowship offers a unique opportunity to be at the forefront of groundwater technology, gaining experience on projects ranging from groundwater sampling and geophysical imaging in the field, analysis
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image-based phenotyping of fruit quality and yield to improve cataloging and characterization of germplasm holdings. The research will generate publishable methodologies and results that support data
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individuals and as communities comprising larger ecosystems. Traits are also often used as parameters in computer models of terrestrial ecosystems and even the entire Earth System (such as climate models used
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include the development of predictive models for disease resistance, genome-wide association studies to uncover resistance loci, automated phenotyping approaches using image data, and integrative multi
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therapeutics. The experience includes opportunities to learn the operation and upkeep of physiological and cell culture instrumentation, apply quality assurance and quality control practices, and contribute
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concept to prototype testing and calibration. This solid engineering background will be advantageous to the participant in their future career. Mentor(s): The mentor for this opportunity is Samir Trabelsi
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size exclusion chromatography) Conduct protein binding experiments (ELISA or SPR) Develop and optimize protocols for sample preparation and imaging by cryo-EM Collect and analyze cryo-EM data using a
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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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, and trace volatiles Advancement of techniques for Imaging and Visualization Under the guidance of a mentor, you may be involved in some or all of the following: Conducting searches of scientific
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-automated processing pipeline capable of analyzing high-throughput plant phenotyping and soil-sensing data to extract key phenotypic traits. Advancing crop productivity within sustainable cropping systems