Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
) conducts cutting-edge research and development (R&D) for the U.S. Air Force, with products that transition to systems centers and the field. It employs 10,000 people and expends nearly $5 billion per annum
-
areas that support Sandia National Laboratories’ Research Foundations. For information about the Research Foundations, please visit https://www.sandia.gov/research/research-foundations/ . Sandia has as
-
that support Sandia National Laboratories’ Research Foundations. For information about the Research Foundations, please visit https://www.sandia.gov/research/research-foundations/ . Sandia has as its mission
-
areas that support Sandia National Laboratories’ Research Foundations. For information about the Research Foundations, please visit https://www.sandia.gov/research/research-foundations/ . Sandia has as
-
. As a subordinate element of the U.S. Army Medical Research and Development Command (USAMRDC), the institute conducts research for development of medical countermeasures to treat exposure to various
-
Germplasm System - https://www.ars-grin.gov/Collections#plant-germplasm . Our mission is to conserve, document, distribute, characterize, and evaluate crop germplasm for crop improvement research. Our
-
communication, methods development, presentation and communication skills. In addition, you will collaborate with a diverse team of researchers with the common goal of characterizing chemicals and understanding
-
. These include, but are not limited to: Writing proposals under guidance of senior scientist Learning all aspects of the drug development process from early discover through pre-clinical trials Performing
-
About ARD ARL’s Army Research Directorate (ARD) focuses on exploiting concept development, discovery, technology development, and transition of the most promising disruptive science and technology to
-
Organization DEVCOM Army Research Laboratory Reference Code ARL-C-CISD-300144 Description About the Research Current approaches optimize machine learning training largely by exploiting Deep Neural Networks (DNNs) sparsity. The compute-intensive floating-point 32-bit representation represents...