Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Oak Ridge National Laboratory
- EPFL
- NEW YORK UNIVERSITY ABU DHABI
- AALTO UNIVERSITY
- Aarhus University
- Argonne
- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
- SciLifeLab
- Stanford University
- University of North Carolina at Chapel Hill
- Utrecht University
- Yale University
- ;
- Baylor College of Medicine
- Eindhoven University of Technology (TU/e)
- European Space Agency
- Forschungszentrum Jülich
- Fundació per a la Universitat Oberta de Catalunya
- Harvard University
- Inria, the French national research institute for the digital sciences
- Istituto Italiano di Tecnologia
- KTH Royal Institute of Technology
- KU LEUVEN
- Lehigh University
- Max Planck Institute for Gravitational Physics, Potsdam-Golm
- Mohamed bin Zayed University of Artificial Intelligence
- Northeastern University
- Sandia National Laboratories
- Stony Brook University
- Texas A&M University
- The Ohio State University
- University of California
- University of California, Los Angeles
- University of Florida
- University of Minnesota
- University of South Carolina
- 26 more »
- « less
-
Field
-
/ JAX, and scaling deep learning models to large GPU-based machines Knowledge in training domain specific AI foundation models built using transformers, GNN and diffusion Technical knowledge in using HPC
-
extracting transport properties from molecular dynamics trajectories. ● Experience with GPU-accelerated machine learning frameworks (for example CUDA, PyTorch, or GPU-enabled LAMMPS). ● Experience
-
machine-learning methods to weather forecasting, climate analysis, or spatial data. Strong background in spatiotemporal modeling, probabilistic prediction, or time-series analysis. Proficiency in Python and
-
Engineering at The Ohio State University conducts interdisciplinary research in scalable software systems, artificial intelligence and machine learning (AI/ML), edge-to-cloud computing platforms, digital
-
Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 10 days ago
inference, including machine-learning methods. Astrophysics of compact objects and binary formation scenarios. Cosmography with gravitational waves: dark energy, dark matter and gravitational lensing. Tests
-
machine learning, topological quantum materials, and/or related areas. The successful candidate will have access to HiPerGator, the fastest university-owned supercomputer in the United States (TOP500
-
. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and
-
interpreting results, and benchmarking brain-inspired architectures against conventional machine learning methods. You are also expected to actively participate in academic discussions with supervisors at KTH
-
. An interdisciplinary interdisciplinary environment, in which the candidate will be able to exchange across research fields (machine learning, bioinformatics, biology, and quantitative genetics) and applications (plant
-
includes: Strong programming skills, particularly in Python. Proficiency in other languages is a plus. Strong knowledge of and experience in machine learning and deep learning techniques, and relevant