Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Harvard University
- National University of Singapore
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Simons Foundation;
- Singapore University of Technology & Design
- UNIVERSITY OF SURREY
- University of Oslo
- Aarhus University
- CRANFIELD UNIVERSITY
- Center for Devices and Radiological Health (CDRH)
- City of Hope
- Dana-Farber Cancer Institute (DFCI)
- Florida Atlantic University
- Georgia Southern University
- Hong Kong Polytechnic University
- INESC TEC
- Imperial College London
- NTNU Norwegian University of Science and Technology
- Nanyang Technological University
- Oden Institute for Computational Engineering and Sciences
- SUNY University at Buffalo
- UCL;
- University of California
- University of Idaho
- University of Maryland, Baltimore
- University of Texas Rio Grande Valley
- University of Waterloo
- Zintellect
- 18 more »
- « less
-
Field
-
research. BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent compute capacity in total across
-
experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
-
Processing Unit (GPU) hardware. Working Conditions Needs to be able to successfully perform all required duties. Office/research environment; some travel and weekend work is required. UTRGV is a distributed
-
of environmental factors of 60,000 subjects across multiple time points. Our research laboratory has great computing capacity, including multiple H100 and A100 GPU systems for deep learning, and computing clusters
-
for recruitment positions and for general criteria for the position. Preferred selection criteria Knowledge of in Norwegian/Scandinavian language Experience with GPU based systems Experience with HPC based
-
experience with probabilistic or computational modelling. Experience with language model evaluation, cognitive modelling, reinforcement learning, goal-directed behaviour, learning theory or large-scale GPU
-
parallel programming and/or high-performance computing, particularly on GPU or FPGA architectures; Knowledge of compression techniques, including predictive coding, filter banks, transforms, and statistical
-
. Experience in hardware–software integration, GPU/FPGA acceleration, or translation of research into prototype systems would be an added advantage. Ability to work independently while contributing effectively
-
Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 3 months ago
development, including grant writing and academic presentation. Have access to the largest academic computing cluster in the world, including the largest GPU cluster. Application Materials Applicants should
-
expertise in optimisation; Computer Science, with expertise in design and analysis of algorithms and high-performance (GPU) computing; Industrial and Systems Engineering, with AI in process mapping and Conops