Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- NEW YORK UNIVERSITY ABU DHABI
- Lunds universitet
- Forschungszentrum Jülich
- Northeastern University
- Academia Sinica
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- SUNY Polytechnic Institute
- AI4I
- Argonne
- Brookhaven National Laboratory
- Chalmers University of Technology
- Inria, the French national research institute for the digital sciences
- Istituto Italiano di Tecnologia
- Itä-Suomen yliopisto
- La Rochelle Université
- Luxembourg Institute of Health
- Max Planck Institute for Psycholinguistics
- Nature Careers
- RIKEN
- Rutgers University
- Sano Centre for Computational Personalized Medicine
- TU Wien
- Technical University of Munich
- The University of Arizona
- Universite de Montpellier
- University of California
- University of Lund
- University of North Carolina at Chapel Hill
- University of Turku
- University of Utah
- l'institut du thorax, INSERM, CNRS, Nantes Université
- 22 more »
- « less
-
Field
-
conducted implementations of algorithms and simulations using contemporary GPU hardware, or Profound knowledge and experience of the DUNE software environment (https://dune-project.org/ ) (knowledge and
-
programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
-
), with collaboration from PhD students and external partners. The researcher will benefit from an active local community in AI and access to GPU computing infrastructure. Where to apply Website https
-
contemporary GPU hardware, or Profound knowledge and experience of the DUNE software environment (https://dune-project.org/) (knowledge and experience with DUNE-FEM is a merit). You have very good oral and
-
candidate, skilled in numerical model development (programming in FORTRAN, numerical methods, HPC environment). Experience in numerical methods on unstructured grids and/or GPU would be strong assets
-
their publications Experience programming GPUs with CUDA, SYCL, HIP or OpenMP Experience using and developing code with AMReX Experience in performance engineering to improve code scalability and reduce time-to
-
programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
-
frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
-
will benefit from the Jean Zay supercomputer to perform intensive GPU calculations but also MARBEC/LIRMM GPU shared resources (https://umr-marbec.fr/recherche/dispositifs-de-recherche/den/ ). His/her
-
funded by the EU FP7 program, H2020 program and the European Space Agency (ESA). For further information, you may check: www.securityandtrust.lu The SigCom research group carries out research activities in