Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Oak Ridge National Laboratory
- Argonne
- Nature Careers
- CNRS
- Duke University
- Technical University of Munich
- NEW YORK UNIVERSITY ABU DHABI
- Stanford University
- Aarhus University
- Harvard University
- New York University
- Rutgers University
- SUNY Polytechnic Institute
- Technical University of Denmark
- Texas A&M University
- University of Luxembourg
- University of Miami
- University of North Carolina at Chapel Hill
- AI4I
- Brookhaven National Laboratory
- Chalmers University of Technology
- Dublin City University
- ELETTRA - SINCROTRONE TRIESTE S.C.P.A.
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- FAPESP - São Paulo Research Foundation
- Forschungszentrum Jülich
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Max Planck Institute for Solar System Research, Göttingen
- Max Planck Institute of Animal Behavior, Radolfzell / Konstanz
- McGill University
- Nagoya University
- Northeastern University
- Sandia National Laboratories
- University of Basel
- University of Central Florida
- University of Jyväskylä
- University of Liverpool
- University of Nebraska Medical Center
- University of New Hampshire
- University of Turku
- University of Utah
- Université côte d'azur
- Utrecht University
- VIB
- 35 more »
- « less
-
Field
-
models on GPU-based systems; familiarity with HPC environments is an advantage Interest in interdisciplinary research at the interface of AI and genomics; prior experience with biological data
-
for embedded and GPU platforms. Collaborate with ARSPECTRA engineers and surgeons to create a complete AR guidance pipeline : tracking, SLAM, gaze, user interface Your profile PhD in machine learning
-
RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent written and oral communication skills. Motivated self-starter with
-
developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
-
-on experience developing generative models Is highly proficient in PyTorch and/or JAX Has experience training large-scale neural networks on HPC or GPU clusters Has experience with representation learning and
-
transformer architectures (e.g., ViT/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g
-
chemistry and experience with quantum chemistry packages (e.g., Molpro, NWChem) Strong skills in developing and implementing computational and numerical methods; familiarity with parallel computing on CPU/GPU
-
-on experience developing generative models Is highly proficient in PyTorch and/or JAX Has experience training large-scale neural networks on HPC or GPU clusters Has experience with representation learning and
-
(static and dynamic photochemistry, heterogeneous catalysis, modeling of interfaces and ionic liquids). It benefits from access to the CBPSMN mesocenter, with a large amount CPUs and GPUs facilities. In
-
required to maintain a new GPU cluster at KMI, spending no more than 20% of the FTE. The anticipated starting date is between April 2026 to October 2026. The appointment will be initially 2 years and may be