Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
be in English or include an official English translation. If you have questions about the application process, contact NETLinfo@orau.org . After you have submitted an application in Zintellect, you may
-
contamination in corn remains one of the most persistent threats to U.S. agriculture, with significant implications for food safety and crop quality. Current satellite imaging technologies lack ability to detect
-
of incorporating sensors, spectroscopy, imaging, and machine learning techniques into the postharvest processing workflows and/or pre-harvest evaluation of food quality and safety. The participant will have the
-
be in English or include an official English translation. If you have questions about the application process, contact NETLinfo@orau.org . After you have submitted an application in Zintellect, you may
-
-liquid interface in vitro models of the human lung Gaining experience preparing routine chemical and drug solutions Conducting in-depth analysis of high-throughput data Interpreting fluorescent image
-
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
-
-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
-
in preharvest and post-harvest production and processing. This project will focus primarily on safety and quality inspection using spectral imaging techniques such as fluorescence, reflectance, and
-
this fellowship, you will participate in research projects involving canine biometric data, looking for novel ways to identify and individuate dogs using neural networks, local feature mapping, image classifiers
-
machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of