Sort by
Refine Your Search
-
areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
-
, economic evaluation, and surveillance to learn how to operationalize, and when needed, improve analytical tools. Research activities will support rapid risk assessment, emergency preparedness, and
-
the relative importance of processes in simulating the CMRB agroecosystem. Learning Objectives: Under the guidance of the mentor, the participant will: Learn how cropping system design must align with local soil
-
. Research Project: Joining a team of landscape and fire ecologists to learn about and support geospatial analysis of fire mitigation implementation in the highly fire prone lands of Kona and Kohala on Hawaii
-
research applying artificial intelligence (AI) and machine learning (ML) techniques to analyze cervid movement patterns. GPS telemetry data obtained from free ranging cervids will be used by the participant
-
expected to learn both independently and collaboratively within a multidisciplinary research team, contribute to experimental design and data analysis, publish findings in peer-reviewed journals, and
-
to exploit in their projects. Characterization of the alfalfa collection can aid in effective management of this important resource while improving and promoting its use by stakeholders. Learning Objectives
-
to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
-
conditions. Anticipated outcomes of the project include criteria for selection of fungal genotypes that will be developed into new biocontrol products for mitigation of crop aflatoxin contamination. Learning
-
decision-making by forest managers, planners, and policy makers. This project will inform the Forest Service’s Resources Planning Act (RPA) Assessment. Learning Objectives: The participant will have the