Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- Carnegie Mellon University
- Oak Ridge National Laboratory
- Aalborg University
- Delft University of Technology (TU Delft)
- KTH Royal Institute of Technology
- Stony Brook University
- CNRS
- Eindhoven University of Technology (TU/e)
- Helmholtz Association of German Research Centres
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Northeastern University
- Technical University of Munich
- AALTO UNIVERSITY
- Argonne
- CNRS-LMA
- DURHAM UNIVERSITY
- Deutsches Elektronen-Synchrotron DESY
- Durham University
- EPFL
- Harvard University
- King's College London
- Max Planck Institute for Plasma Physics (Garching), Garching
- Michigan State University
- NEW YORK UNIVERSITY ABU DHABI
- National Aeronautics and Space Administration (NASA)
- National Energy Technology Laboratory (NETL)
- Pennsylvania State University
- SUNY University at Buffalo
- Singapore-MIT Alliance for Research and Technology
- Technical University Of Denmark
- The University of Western Australia
- UNIVERSITY OF VIENNA
- University of Borås
- University of Minnesota
- University of New Hampshire
- University of North Carolina at Charlotte
- University of Oxford
- University of Oxford;
- Université de Limoges
- Virginia Tech
- 30 more »
- « less
-
Field
-
modeling and simulation • Development in Finite element and alternative discretization methods (e.g. Lattice Boltzmann methods) • High-dimensional algorithms and high-performance computing
-
., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration and haptics feedback in
-
(photolithography, metal evaporation, etching) Experience with packaging schemes such as flip-chip bonding, anisotropic conductive film bonding and wire bonding Finite element Method (FEM) simulations (MEMS, Electro
-
by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
-
include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory
-
-performance computing. It aims to improve the performance of the matrix-free finite-element-based framework HyTeG, in particular by techniques for data reduction through surrogate operators. Furthermore, we aim