Sort by
Refine Your Search
-
Employer
- University of North Carolina at Chapel Hill
- Oak Ridge National Laboratory
- Argonne
- National Energy Technology Laboratory (NETL)
- The University of Arizona
- University of Miami
- Northeastern University
- Rutgers University
- Texas A&M University
- University of Minnesota
- Virginia Tech
- Montana State University
- SUNY University at Buffalo
- Stanford University
- Texas A&M AgriLife
- U.S. Department of Energy (DOE)
- Lawrence Berkeley National Laboratory
- Pennsylvania State University
- University of Kentucky
- Zintellect
- Brookhaven National Laboratory
- Carnegie Mellon University
- Duke University
- St Jude Children's Research Hospital
- The Ohio State University
- University of California
- University of Maryland, Baltimore
- University of Texas at Tyler
- Boise State University
- Boston University
- Cornell University
- Delaware State University
- Eli Lilly and Company
- Iowa State University
- Michigan Technological University
- National Aeronautics and Space Administration (NASA)
- Texas A&m Engineering
- University of California, Los Angeles
- University of Colorado
- University of Florida
- University of Illinois
- University of Kansas Medical Center
- University of Nevada Las Vegas
- University of New Hampshire – Main Campus
- University of North Carolina at Greensboro
- University of North Texas at Dallas
- University of Texas at Arlington
- University of Utah
- University of Washington
- Villanova University
- 40 more »
- « less
-
Field
-
, primarily for recycling used nuclear fuel to support the deployment of advanced reactors. The selected candidate will develop and optimize novel separations chemistries to recover actinide and rare earth
-
method development and large-scale research facilities. Essential Duties and Responsibilities Develop workflows to improve models and maps to optimize likelihood for ligand placement Develop AI/ML methods
-
-throughput data, identify differentially expressed genes, explore protein interaction networks, and perform pathway and functional enrichment analyses. Responsibilities also include developing and optimizing
-
the nexus of AI, operations research and decision making and their applications to workforce policy and reskilling. The project builds on ongoing work using optimization-based models to predict future skill
-
. Mentor and support junior lab members, including research technologists, students, and trainees, and contribute to a collaborative lab environment. Special Skills, Knowledge, and Abilities: Strong
-
, collaborative meetings, and scientific conferences. Mentor junior lab members and contribute to a collaborative wet-dry lab environment. Special Skills, Knowledge, and Abilities: Strong background in quantitative
-
capabilities in support of dramatic advances in our understanding of the physical world and using that knowledge to address the most pressing national and international concerns. It delivers leadership- class
-
network optimization for 6G/FutureG wireless networks especially on the Internet of Intelligent Things under the supervision of Dr. Lingjia Liu (https://lingjialiu.ece.vt.edu). Successful candidates will
-
modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
-
structural findings with biochemical and genetic data to define mechanism of action. Develop and optimize workflows for sample preparation, grid screening, and high-throughput image acquisition. Collaborate