Sort by
Refine Your Search
-
Listed
-
Employer
- Argonne
- Stanford University
- University of North Carolina at Chapel Hill
- Oak Ridge National Laboratory
- University of Washington
- Texas A&M University
- University of Houston Central Campus
- Brookhaven Lab
- Pennsylvania State University
- University of Maryland, Baltimore
- Stony Brook University
- Nature Careers
- Northeastern University
- University of Minnesota
- Virginia Tech
- Baylor College of Medicine
- DePaul University
- Indiana University
- New York University
- The Ohio State University
- The University of Arizona
- University of Central Florida
- University of Florida
- University of Houston
- University of North Texas at Dallas
- University of Oklahoma
- University of Virginia
- Yale University
- Broad Institute of MIT and Harvard
- California Institute of Technology
- Carnegie Mellon University
- Cornell University
- Eastern Kentucky University
- Embry-Riddle Aeronautical University
- Fred Hutchinson Cancer Center
- Georgia Institute of Technology
- Harvard University
- Los Alamos National Laboratory
- Loyola University
- Michigan Technological University
- Missouri University of Science and Technology
- National Aeronautics and Space Administration (NASA)
- National Renewable Energy Laboratory NREL
- Ohio University
- Princeton University
- Purdue University
- SUNY University at Buffalo
- Texas A&M AgriLife
- The University of Iowa
- The University of North Carolina at Chapel Hill
- University of California Irvine
- University of California, Merced
- University of Delaware
- University of Massachusetts
- University of Massachusetts Medical School
- University of South Carolina
- University of Southern California
- University of Texas at Arlington
- Zintellect
- 49 more »
- « less
-
Field
-
sparse algorithms. The successful candidate will contribute to advancing secure, trustworthy, and efficient AI solutions for scientific applications. Key responsibilities include developing state
-
development of detectors sensitive to ultra-high dose rates. Developments of computation methods for small-field dosimetry, radiation detection systems used in photon, proton, and electron beam radiation
-
The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
development of data processing tools. The position is for one year with the possibility of reappointment for an additional year. It will involve developing, implementing, and validating novel algorithms
-
leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
-
magnetometry measurement and analysis of the Nab spectrometer magnetic fields, help develop the BL3 DAQ and algorithms, carry out Monte Carlo simulations for Nab and BL3, and help undergraduates at EKU finish
-
Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
-
, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
-
, while contributing to development efforts from algorithm design and testing, synthetic data generation, user interfaces, and model deployment. Initial appointments will be for one year with
-
. Develops understanding and skills to allow for completion of assignments that cross fields of specialization. Develops leadership and management skills. 1. Receives/Reviews progress and evaluates results
-
of pediatric cancer patients and discover the impact of therapeutic exposure on development of secondary neoplasms in adult survivors. Position Responsibilities: Evaluate bulk-tumor deconvolution algorithms