Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Oak Ridge National Laboratory
- NEW YORK UNIVERSITY ABU DHABI
- CNRS
- Argonne
- Lunds universitet
- Nature Careers
- Northeastern University
- Aalborg University
- Forschungszentrum Jülich
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Technical University of Munich
- University of California
- Academia Sinica
- ICN2
- Lawrence Berkeley National Laboratory
- SUNY Polytechnic Institute
- Stanford University
- Technical University of Denmark
- University of Kansas
- University of Lund
- University of North Carolina at Chapel Hill
- Yale University
- AI4I
- Brookhaven National Laboratory
- Chalmers University of Technology
- Durham University
- Embry-Riddle Aeronautical University
- Empa
- Inria, the French national research institute for the digital sciences
- Istituto Italiano di Tecnologia
- Itä-Suomen yliopisto
- KINGS COLLEGE LONDON
- King's College London
- La Rochelle Université
- Luxembourg Institute of Health
- Max Planck Institute for Gravitational Physics, Potsdam-Golm
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Psycholinguistics
- Max Planck Institute for Psycholinguistics; today published
- McGill University
- RIKEN
- Rutgers University
- Sano Centre for Computational Personalized Medicine
- TU Wien
- The University of Arizona
- The University of Edinburgh;
- Universite de Montpellier
- University of Antwerp
- University of Miami
- University of New Hampshire
- University of New Hampshire – Main Campus
- University of Turku
- University of Utah
- l'institut du thorax, INSERM, CNRS, Nantes Université
- 44 more »
- « less
-
Field
-
%). You will work on the extension of the DUNE-FEM package to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering
-
scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs
-
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
-
to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering structure preserving Finite Element methods for multiphase flows
-
algorithms. The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters
-
time steps, will be explored. For these two projects, the GPU-based version of SCHISM under development will also be tested. Type of recruitment 12-month postdoctoral contract based in La Rochelle (17
-
-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
-
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
-
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
-
-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will