Sort by
Refine Your Search
-
Listed
-
Employer
- Oak Ridge National Laboratory
- Stony Brook University
- University of Central Florida
- Stanford University
- University of North Carolina at Chapel Hill
- Cornell University
- Duke University
- Florida Gulf Coast University
- Florida International University
- Princeton University
- Rutgers University
- University of Maine
- University of Texas at Austin
- University of Utah
- Argonne
- Arizona State University
- Cal Poly Pomona
- Kennesaw State University
- Los Alamos National Laboratory
- SUNY University at Buffalo
- University of California Davis
- University of California Irvine
- University of Maryland
- University of Massachusetts
- University of Miami
- University of Nebraska Medical Center
- University of Nevada, Reno
- University of South Carolina
- University of Texas at Arlington
- Virginia Tech
- 20 more »
- « less
-
Field
-
retinal tissue dissection, immunohistochemical and molecular assays, confocal imaging, and basic analysis of imaging data. The candidate will help with tissue processing and data collection across multiple
-
and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here in New York, across the nation, and around the world. Starting Date: As soon as
-
to model equity in action in engineering through redefining what is valued; redefining what it means to have impact, and for whom; reaching target audiences, stakeholders, and the community via innovative
-
science simulations and excellent writing skills, as evidenced by multiple peer-reviewed publications, are preferred. -Curiosity and passion for computer-driven problem solving and an ability to work
-
-doing approach and Teacher Scholar Model . The university is noted for its scenic and historic 1,400-acre campus, which was once the winter ranch of cereal magnate W.K. Kellogg. We acknowledge that Cal
-
material. Thermal simulations to study the transient thermal performance of the materials is required. 3. Neural network ML modeling to predict the RF device performance and failure mechanisms. a