Sort by
Refine Your Search
-
Listed
-
Employer
- University of North Carolina at Chapel Hill
- Argonne
- Oak Ridge National Laboratory
- SUNY University at Buffalo
- Stanford University
- University of Washington
- The Ohio State University
- Brookhaven Lab
- Carnegie Mellon University
- Duke University
- University at Buffalo
- University of Minnesota
- Cornell University
- Northeastern University
- Princeton University
- The University of Iowa
- University of Arkansas
- Virginia Tech
- Drexel University
- Johns Hopkins University
- National Aeronautics and Space Administration (NASA)
- National Renewable Energy Laboratory NREL
- Nature Careers
- Rutgers University
- University of California, Merced
- University of Cincinnati
- University of Minnesota Twin Cities
- Washington University in St. Louis
- Baylor College of Medicine
- Brookhaven National Laboratory
- Case Western Reserve University
- Delaware State University
- Emory University
- Indiana University
- Los Alamos National Laboratory
- Loyola University
- Massachusetts Institute of Technology
- Medical College of Wisconsin
- Pennsylvania State University
- Rochester Institute of Technology
- Texas A&M AgriLife
- Texas A&M University System
- The University of Arizona
- The University of Chicago
- University of California Berkeley
- University of Chicago
- University of Colorado
- University of Delaware
- University of Denver
- University of Florida
- University of Illinois - Chicago
- University of Illinois at Chicago
- University of Kansas Medical Center
- University of Miami
- University of Oregon
- University of St. Thomas
- University of Texas at Arlington
- University of Texas at Austin
- University of Utah
- University of Virginia
- Yale University
- 51 more »
- « less
-
Field
-
. The work will apply state-of-the-art three-dimensional atmospheric chemistry and circulation models, together with advanced statistical techniques (optimal Bayesian, Markov Chain-MonteCarlo, etc.) to solve
-
, and network optimization for 6G networks and FutureG wireless networks. Successful candidates will have the chance to work with top-notch researchers from both academia and industry on future wireless
-
, CT, and other imaging techniques. Design and optimize multiparametric models to analyze complex imaging datasets and extract clinically relevant features. Develop and optimize newer clinically relevant
-
probes. The postdoc will play a key role in designing and optimizing imaging devices, integrating hardware and software, and collaborating with a multidisciplinary team of clinicians, engineers, and basic
-
, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
-
, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
-
system optimization for remote construction. This position will focus on advancing research in construction assembly science and technology, logistics optimization, and real-time communication frameworks
-
optimization technologies are revolutionizing the way power grid is operated and planned. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using
-
scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and machine learning
-
. Minimum Qualifications PhD in Communication, Psychology, or related field conferred within the last five years. Excellent oral and written communication skills. Preferred Qualifications Physical Demands