Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
as safely and securely as possible. Learning Objectives: Under the guidance of a mentor, you will learn from DRSC’s Biosafety, Science, Training, and Expertise Branch while participating in a variety
-
, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural
-
expensive and dangerous health threats, and responds when these arise. Research Project: This project will be across teams in the branch to provide an opportunity to learn about the needs of priority
-
, Training, and Expertise Branch to engage in and learn from a project supporting training programs for new and experienced DRSC inspectors and auditors within FSAP, IPP, and NAC. Learning Objectives: During
-
development, and evaluation, by learning to implement automation, integrating data across systems (SharePoint, Teams, Salesforce, and 1CDP (Palantir System), and creating operational dashboards under
-
quality and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how physical and chemical fiber parameters relate to dye uptake behavior, dyebath exhaustion, color
-
emerging technologies, transportation data, policy, research and all modes of transportation across the Department. As a Fellow, you will learn to facilitate the transformation of our transportation system
-
well as communicate with research networks within the scientific community. Learning Objectives: As part of this learning experience, you may: Learn how grapevine populations and germplasm are evaluated to identify
-
public health preparedness, laboratory biosafety and biosecurity, regulatory oversight, and risk reduction. Under the guidance of a mentor, you will learn from DRSC's Policy and Communications Team engaged
-
-quality issues in bulk storage and food facilities. You will join and learn from a community of scientists and post-docs in the unit engaged in efforts to integrate and analyze data from volatile-gas