Sort by
Refine Your Search
-
Employer
- University of North Carolina at Chapel Hill
- Argonne
- National Aeronautics and Space Administration (NASA)
- Princeton University
- Oak Ridge National Laboratory
- Baylor College of Medicine
- Cornell University
- Los Alamos National Laboratory
- New York University
- Purdue University
- Texas A&M University
- The Ohio State University
- The University of Iowa
- University of Arkansas
- University of Cincinnati
- University of Kansas
- University of Minnesota
- University of Minnesota Twin Cities
- University of South Carolina
- University of Texas at Arlington
- University of Virginia
- University of Washington
- Zintellect
- 13 more »
- « less
-
Field
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
other sciences. A strong managerial, administrative, and technical staff supports this instructional mission. Duties of these employees range from budget planning and management for the numerous research
-
access to state-of-the-art numerical models and high-performance computing systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and
-
scientist and engineers at the University of Cincinnati as well as Procter & Gamble across numerous scientific domains. Utilize mathematical modeling, statistical techniques, chemistry, physics, and
-
algorithms and codes for AI-enabled digital twin technologies. Design advanced numerical algorithms for partial differential equations and optimization problems related to digital twin technology. Implement
-
requires not only expertise in LLMs and machine learning but also an understanding of the unique challenges posed by scientific data, which often includes large-scale numerical datasets, complex simulations
-
Systems will participate in the research efforts of developing systems integration, analysis, design, control, and/or optimization models and algorithms for smart energy systems to enable smart and healthy
-
in adaptive immune systems (e.g., co-evolution of bacteria and phages, as well as T and B cells with pathogens). • Physics-informed machine learning of biophysical systems (e.g., developing optimal
-
that integrate simulation, machine learning, and data analysis. Numerical optimization methods (e.g. machine learning including deep neural networks, reinforcement learning, data mining, genetic algorithms
-
such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
-
, collaboration, high-quality work, and real-world problem solving. This position will conduct numerical simulation studies, work on research projects with external partners, mentor and guide graduate student