Sort by
Refine Your Search
-
Listed
-
Employer
- New York University
- The Ohio State University
- Duke University
- Georgia Southern University
- Kennesaw State University
- National Aeronautics and Space Administration (NASA)
- Pennsylvania State University
- Stanford University
- Stony Brook University
- Texas A&M AgriLife
- University of Maine
- University of Miami
- University of Nevada Las Vegas
- University of Nevada, Reno
- University of South Carolina
- University of Texas at Dallas
- University of Washington
- Virginia Tech
- 8 more »
- « less
-
Field
-
National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 3 days ago
, machine learning and statistical methods to elevate impacts research. There is also opportunity to work at the nexus of water and agriculture, as well as in risk management for suburban landscapes. Location
-
Post-Doctoral Associate in the Center for Translational Medical Devices (CENTMED) - Dr. Panče Naumov
status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status
-
. The findings will also support improved treatment design and layout, real-time decision-making during wildfire incidents, and the adaptive management and monitoring of fuel treatment investments
-
for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
-
and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive
-
project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
-
project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
-
monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning. Develop and evaluate GPT-powered AI
-
, whether actual or perceived by others (including service-connected disabilities), gender (including pregnancy related conditions), military status or military obligations, sexual orientation, gender
-
advanced machine learning and deep learning tools to decode the complexity of immune–tumor interactions, integrate multi-omics data at scale, and predict patient responses to therapy. The center works at