Sort by
Refine Your Search
- 
                Listed
- 
                Employer- Oak Ridge National Laboratory
- Argonne
- University of Washington
- Stanford University
- University of North Carolina at Chapel Hill
- Texas A&M University
- Nature Careers
- Stony Brook University
- National Aeronautics and Space Administration (NASA)
- Northeastern University
- Baylor College of Medicine
- The University of Arizona
- University of Maryland, Baltimore
- University of Minnesota
- Texas A&M AgriLife
- The University of North Carolina at Chapel Hill
- University of Central Florida
- University of Houston Central Campus
- Virginia Tech
- Broad Institute of MIT and Harvard
- Brookhaven Lab
- Brookhaven National Laboratory
- DePaul University
- George Washington University
- Indiana University
- Lawrence Berkeley National Laboratory
- Pennsylvania State University
- Princeton University
- University of California
- University of Florida
- University of Houston
- University of Oklahoma
- University of Virginia
- Yale University
- California Institute of Technology
- Caltech
- Carnegie Mellon University
- Cornell University
- Dartmouth College
- Eastern Kentucky University
- Georgia Institute of Technology
- Harvard University
- Loyola University
- Massachusetts Institute of Technology
- Michigan Technological University
- Missouri University of Science and Technology
- New York University
- Northwestern University
- The Ohio State University
- University of California Berkeley
- University of California Merced
- University of California, Merced
- University of Delaware
- University of Illinois at Chicago
- University of Kentucky
- University of Massachusetts
- University of Massachusetts Medical School
- University of Miami
- University of Nevada, Reno
- University of North Carolina at Charlotte
- University of South Carolina
- University of Texas at Dallas
- Washington University in St. Louis
- Zintellect
- 54 more »
- « less
 
- 
                Field
- 
                
                
                industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE 
- 
                
                
                , Weight, and Power) DAS system. - Develop calibration and processing pipelines for stable, low-noise operation. - Plan and run environmental tests (thermal/vacuum, vibration) and analogue field trials 
- 
                
                
                machine learning, statistics, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a 
- 
                
                
                outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision 
- 
                
                
                optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise 
- 
                
                The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 7 days ago, and medicine. Key Responsibilities Collaborate with researchers to design, develop, and refine large language and generative models. Develop novel algorithms for generative modeling tasks and optimize 
- 
                
                
                typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical 
- 
                
                
                , lead large-scale benchmarking across the full stack, and develop scalable classical simulations (e.g., tensor networks)—including performance bounds beyond brute-force classical simulability. This role 
- 
                
                
                the full stack, and develop scalable classical simulations (e.g., tensor networks)--including performance bounds beyond brute-force classical simulability. This role is deeply collaborative with the Advanced 
- 
                
                
                to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems