Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Sheffield
- University of Oxford
- DURHAM UNIVERSITY
- Durham University
- Imperial College London
- Imperial College London;
- KINGS COLLEGE LONDON
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Edinburgh;
- University of Birmingham;
- Abertay University
- Abertay University;
- Cardiff University
- Durham University;
- EMBL-EBI - European Bioinformatics Institute
- London School of Economics and Political Science;
- Medical Research Council
- Nature Careers
- Northumbria University;
- Queen Mary University of London;
- Swansea University
- Technical University of Denmark
- The University of Manchester;
- UCL;
- UNIVERSITY OF VIENNA
- University of Bath
- University of Bristol
- University of Bristol;
- University of East Anglia
- University of Exeter
- University of Glasgow
- University of London
- 22 more »
- « less
-
Field
-
Department of Computing is seeking a dedicated and skilled individual to manage our internal large-scale GPU infrastructure and cloud facilities. The Department of Computing wishes to recruit a
-
Department of Computing is seeking a dedicated and skilled individual to manage our internal large-scale GPU infrastructure and cloud facilities. About the role The Department of Computing wishes
-
Shifting bits: Adaptive numerical precision for GPU software in particle physics and beyond (S3.5-COM-Richmond) School of Computer Science PhD Research Project Competition Funded Students Worldwide
-
Shifting bits: Adaptive numerical precision for GPU software in particle physics and beyond (S3.5-COM-Richmond)
-
computing and the use of GPU clusters. Entry Requirements Acceptable first degree - Computer Science/Physics/Maths The standard minimum entry requirement is 2:1. First class in bachelor degree or a master
-
for heterogeneousCPU/GPU architectures, with a strong emphasis on performance profiling and optimisation. You will manage defined tasks and milestones and collaborate closely with colleagues across the consortium
-
simulation workload and update the solver data structures when the mesh changes. These approaches would be applied on modern large-scale heterogeneous parallel computing environments where both CPUs and GPUs
-
, mobile platforms, industrial sensors/cameras, GPU workstations, and cloud platforms. Training covers research methods, scientific writing, open-source best practices, and impact/engagement. You’ll be
-
Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
-
of research computing at LSE. Your expertise will be key in future-proofing our research hardware environment, ensuring high availability, scalability and security across HPC clusters; GPU acceleration, high