Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Forschungszentrum Jülich
- IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava
- SciLifeLab
- CNRS
- AIT Austrian Institute of Technology
- Delft University of Technology (TU Delft)
- Dublin City University
- Electronics and Informatics Department
- Inria, the French national research institute for the digital sciences
- Leibniz
- National Renewable Energy Laboratory NREL
- Reykjavik University
- Technical University of Munich
- Umeå University
- University of Florida
- University of Luxembourg
- University of Nottingham
- University of Nottingham;
- University of Plymouth
- University of Southern Denmark
- VIB
- Vrije Universiteit Brussel (VUB)
- 13 more »
- « less
-
Field
-
sciences Collaboration with experts in lab science, medicine, and machine learning Modern GPU compute infrastructure A chance to contribute to cutting-edge research with real-world impact Who you are Strong
-
processing, computer vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. The University may permit
-
Agent records (using FreezerPro). Required expertise: State-of-the-art expertise in long-read sequencing technologies and associated bioinformatics pipelines, including proficiency with GPU-enabled Oxford
-
across multiple data modalities Manage HPC resources and job scheduling on NAISS Arrhenius CPU and GPU partitions Requirements To meet the entry requirements for doctoral studies, you must hold a Master’s
-
for archiving, indexing and visualization. Our hardware encompasses CPU and GPU-nodes, and software will be designed for both multithreading and horizontal scaling. The PhD student will become part of
-
will also collaborate with a postdoctoral researcher and another PhD candidate on creating new GPU-enabled pharmacophore searching algorithms. Prospective validation will be achieved by predicting
-
) Expertise in further programming languages (in particular C++), GPU programming, parallel programming or high-performance computing are highly valued Keen interest in neuroscience is essential Experience with
-
-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
-
this challenge, semiconductor manufacturers have introduced dedicated Neural Processing Units (NPUs), significantly enhancing performance and energy efficiency. AMD, for example, integrates a CPU, NPU, and GPU
-
IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 29 days ago
deployment, · knowledge of GPU computing and large-scale training, · experience working in an HPC environment, · experience with data annotation pipelines or synthetic data generation. We offer: · work in a