Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- ;
- SciLifeLab
- Aalborg University
- DAAD
- Delft University of Technology (TU Delft)
- Radboud University
- ; Loughborough University
- ; The University of Manchester
- ; University of Birmingham
- ; University of Reading
- ; University of Sheffield
- ; University of Southampton
- Biology Centre CAS
- Curtin University
- ETH Zürich
- Forschungszentrum Jülich
- IMDEA Networks Institute
- IMT Atlantique
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Nature Careers
- Swansea University
- University of Antwerp
- University of Iceland, School of Engineering and Natural Sciences
- 13 more »
- « less
-
Field
-
analysed in a standard web browser. HiPIMS computations can be executed on local GPUs or through cloud-based GPU services, empowering users to conduct large-scale fast flood simulations without worrying
-
performance and reliability targets. Cluster-Based Training & Optimization Train large-scale CV models on multi-GPU or distributed setups, optimizing hyperparameters and resource usage. Profile training
-
physics, mathematics or any related field. 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
-
GPU NVIDIA H100. Interdisciplinary collaborations with AI researchers and clinicians from NHS hospitals. Participate in large collaborative project funded by the National Institute of Health and Care
-
Units (NPUs), significantly enhancing performance and energy efficiency. AMD, for example, integrates a CPU, NPU, and GPU into its latest Ryzen processors, unlocking new possibilities for on-device AI
-
equivalent degree in physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A
-
Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
-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 life Further training opportunities
-
for collaboration inside and outside of the University. It has access to extensive dedicated computing resources (GPU, large storage). The successful applicant will work under the supervision of Prof. Hain. Please
-
vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
-
Good knowledge of AI and applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience