Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- California Institute of Technology
- Ecole Centrale de Lyon
- Oak Ridge National Laboratory
- Nanyang Technological University
- Nature Careers
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Kansas
- Aalborg University
- CNRS
- Center for Theoretical Physics PAS
- Central China Normal University
- Delft University of Technology (TU Delft); yesterday published
- INSTITUTO DE ASTROFISICA DE CANARIAS (IAC) RESEARCH DIVISION
- Lawrence Berkeley National Laboratory
- Umeå universitet stipendiemodul
- University of California
- University of Cambridge;
- University of Southern California
- University of Southern California (USC)
- Université Savoie Mont Blanc
- Virginia Tech
- 12 more »
- « less
-
Field
-
of interpretability methods to ensure ML outputs are meaningful in scientific contexts. Preferred: Background in biomedical data, healthcare, or AI for life sciences. Experience with parallel computing. Familiarity
-
paralleling SiC MOSFETs and power modules and must have experience with hardware methods to attenuate the oscillations successfully. Your experimental experience must be relevant to the tasks and obtained from
-
University of Southern California (USC) | Los Angeles, California | United States | about 1 month ago
(multiscale, QSP, PBPK, PK-PD).Apply numerical methods, optimization, and parameter estimation to calibrate models to experimental/clinical data.Perform sensitivity and uncertainty analyses to assess robustness
-
students to advance project goals. Provide technical guidance and mentoring on CFD, numerical methods, and high-performance computing workflows. 15% - Publication & Dissemination Prepare and submit
-
, graduate, and undergraduate students to advance project goals. Provide technical guidance and mentoring on CFD, numerical methods, and high-performance computing workflows. 15% - Publication & Dissemination
-
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
-
, 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 large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with
-
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
-
for massively parallel computers. Experience with quantum many-body methods. Preferred Qualifications: A strong computational science background. Familiarity with coupled-cluster method. Understanding