Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Ecole Centrale de Lyon
- Oak Ridge National Laboratory
- Nanyang Technological University
- Nature Careers
- University of Kansas
- CNRS
- Central China Normal University
- Delft University of Technology (TU Delft); yesterday published
- INSTITUTO DE ASTROFISICA DE CANARIAS (IAC) RESEARCH DIVISION
- Lawrence Berkeley National Laboratory
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Umeå universitet stipendiemodul
- University of California
- University of Cambridge;
- University of Southern California
- University of Southern California (USC)
- Université Savoie Mont Blanc
- Virginia Tech
- 9 more »
- « less
-
Field
-
The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher — Scientific Machine Learning (NESAP) to join the Workflow
-
supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
-
image processing and analysis method development. The position builds on the lab's track-record in the field of computational imaging techniques for super-resolution microscopy and image analysis
-
, and a solid understanding of numerical analysis and familiarity with the use of analytical tools. They should also have knowledge and experience in parallel coding and spectral methods. They must have
-
for massively parallel computers. Experience with quantum many-body methods. Preferred Qualifications: A strong computational science background. Familiarity with coupled-cluster method. Understanding
-
for simulating two-phase flows by integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics (CFD) methods. The role focuses on transitioning legacy CFD solvers
-
tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics, or a related numerical field. Programming experience
-
parallel clusters Integrate existing physical models into new software infrastructure for EOS research Benchmark against existing methods and support reproducible, open-science practices Collaborate closely
-
completion) in applied mathematics, computer science, or a closely related field. Strong background in numerical linear algebra, algorithm design, and parallel computing. Proficiency in programming languages
-
opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel