Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- SciLifeLab
- Curtin University
- DAAD
- Delft University of Technology (TU Delft)
- Radboud University
- ; Loughborough University
- ; Swansea University
- ; The University of Manchester
- ; University of Birmingham
- ; University of Exeter
- ; University of Reading
- ; University of Sheffield
- ; University of Southampton
- Forschungszentrum Jülich
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Nature Careers
- Technical University of Munich
- University of New Hampshire – Main Campus
- 8 more »
- « less
-
Field
-
University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 22 hours ago
. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
-
-scale training of a high-performance foundation model using a dedicated GPU cluster Fine-tuning the pretrained model on real-world health data from lifespin’s proprietary database Collaborating closely
-
nature of electroweak symmetry breaking and mass generation in the standard model. We developed state of the art (open source) software working on GPU- and CPU-based supercomputing architectures, and
-
of GPUs and/or time in either training or inference procedures, which pose considerable challenges to both academia and industry for widespread access and deployment. In particular, the sampling process of
-
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
-
networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
-
education in theory and practice of generative modeling, have research experience or education in life science data and have prior experience with remote GPU and HPC services. After the qualification
-
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
-
communications. Evaluation of model performance can be conducted based on the data collected through the water tank. We have the GPU machines ($14k) to develop deep neural networks for underwater communications
-
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