Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- Fraunhofer-Gesellschaft
- Nature Careers
- DAAD
- Leibniz
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Academic Europe
- Heidelberg University
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Humboldt-Universität zu Berlin
- Max Planck Institute for Innovation and Competition, Munich
- Max Planck Institute of Geoanthropology, Jena
- University of Tübingen
- 4 more »
- « less
-
Field
-
Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers to help you balance work and family
-
. Additional languages or experience with libraries for utilizing GPU hardware efficiently, e.g., CUDA, are a plus. Experience in AI programming with, e.g., PyTorch(-DDP), Horovod, or DeepSpeed, and in
-
Implement sustainable and reproducible and FAIR research software engineering practices Collaborate with other HPC facilities and project partners Help evaluate and integrate GPU acceleration and other modern
-
approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
-
Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
collaborators # Ability to set individual goals, self-structure and fulfill milestones # Parallel programming, ideally in C++ and with GPUs # Knowledge with Python # Excellent command of English (spoken and
-
, PyTorch/TensorFlow) experience working with cluster/GPU computing resources is desirable excellent verbal and written communication skills and the ability to work effectively in a collaborative team
-
environment with close collaboration between AI experts and leading clinicians Access to unique, large-scale medical datasets and high-performance computing infrastructure (including NVIDIA B300 GPUs) Funding
-
experience with accelerated architectures (e.g., GPUs or other accelerators) Experience with performance analysis, profiling, and optimization. Note that it is not necessary to fulfil all of these requirements
-
of visualisation, machine learning / AI, and human-computer interaction Very good programming skills (web-based visualisation, Python, and/or GPU programming) First experiences in the participation in research
-
with the domain of optical material behavior acquisition at a decent pace. What you bring to the table Very good C++ programming skills GPU & Shader programming, ideally knowledge of PBR (Physically