Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- Nature Careers
- Oak Ridge National Laboratory
- Argonne
- CNRS
- NEW YORK UNIVERSITY ABU DHABI
- National University of Singapore
- Duke University
- Harvard University
- University of Luxembourg
- Aarhus University
- IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava
- Nanyang Technological University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Stanford University
- Technical University of Munich
- Forschungszentrum Jülich
- Imperial College London
- McGill University
- New York University
- Princeton University
- Rutgers University
- SUNY Polytechnic Institute
- Technical University of Denmark
- University of Miami
- University of Nebraska Medical Center
- University of North Carolina at Chapel Hill
- University of Oslo
- AI4I
- Academic Europe
- Barnard College
- Brookhaven National Laboratory
- Center for Devices and Radiological Health (CDRH)
- Centro de Astrofisica da Universidade do Porto
- Chalmers University of Technology
- Czech Technical University in Prague
- ELETTRA - SINCROTRONE TRIESTE S.C.P.A.
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- Erasmus MC (University Medical Center Rotterdam)
- FAPESP - São Paulo Research Foundation
- FCiências.ID
- Flanders Institute for Biotechnology
- Florida Atlantic University
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Humboldt-Universität zu Berlin
- ICN2
- Imperial College London;
- Jane Street Capital
- LINKS Foundation - Leading Innovation & Knowledge for Society
- Lawrence Berkeley National Laboratory
- Leibniz
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- Macquarie University
- Manchester Metropolitan University
- Max Planck Institute for Solar System Research, Göttingen
- Max Planck Institute of Animal Behavior, Radolfzell / Konstanz
- Nagoya University
- National Renewable Energy Laboratory NREL
- Northeastern University
- Paul Scherrer Institut Villigen
- Sandia National Laboratories
- Texas A&M University
- The California State University
- The University of Alabama
- UiT The Arctic University of Norway
- Umeå universitet stipendiemodul
- University of Basel
- University of Central Florida
- University of Idaho
- University of Jyväskylä
- University of Maryland, Baltimore
- University of New Hampshire
- University of Turku
- University of Utah
- Utrecht University
- VIB
- 66 more »
- « less
-
Field
-
/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g., concept bottlenecks, prototype
-
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
-
disease insights. The lab has state-of-the-art computing capabilities with an in-house cluster serving 80 CPU cores and 1.5TB of RAM, as well as a newly acquired NVIDIA DGX box with eight H100 GPUs and 224
-
managing supercomputer resources Strong skills in algorithm development for large sparse matrices Excellency in programming GPU accelerators from all major vendors Very good command of written and spoken
-
. Programming & Software Development: Proficiency in Python, PyTorch, JAX, or other ML frameworks Computing: Some experience with large-scale datasets, parallel computing, and GPUs/TPUs. Algorithm Development
-
). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as
-
background Preferred Qualifications • Experience with GPU programming, shaders, or advanced rendering techniques • Experience integrating external APIs or live data streams • Background in distributed systems
-
E13) up to 5 years International collaboration to build a large radiotherapy dataset Dedicated GPU infrastructure Strong collaborations within TUM’s AI ecosystem High-impact publication potential
-
). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
-
for accelerators, such as GPUs or FPGAs. Experience in refactoring or porting large codebases (over 100k source lines of code). Background in supporting scientific code on HPC systems or familiarity with components