Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- Forschungszentrum Jülich
- Inria, the French national research institute for the digital sciences
- Medical University of Innsbruck
- University of Nottingham
- AIT Austrian Institute of Technology
- Delft University of Technology (TU Delft)
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- Karolinska Institutet, doctoral positions
- University of Antwerp
- University of Nottingham;
- University of Southern Denmark
- Utrecht University
- VIB
- 5 more »
- « less
-
Field
-
-design with accelerators (FPGAs, GPUs, near-memory systems) to achieve real-time, energy-efficient AI for high-tech industry applications. Work with leading companies like ASMPT and shape the future of AI
-
the development of scalable software tools and pipelines, potentially leveraging GPU/FPGA accelerators. Our aim is to build next-generation molecular atlases for chronic diseases and to improve patient
-
to the development of advanced language models and derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development
-
(€39,005.40 gross/year, 30 hours/week) Access to a modern GPU cluster Conference travel and active support towards publications How to apply Email us with your CV, a GitHub repo or code sample, and a short
-
and clinical MR systems fully dedicated to research, state-of-the-art local and scalable cloud-based compute infrastructure (CPU, GPU) and workshops for mechanical, electrical and electronic development
-
(3–4 years) Salary per university collective agreement (€39,005.40 gross/year, 30 hours/week) Access to a modern GPU cluster Conference travel and active support towards publications How to apply Email
-
using clusters like UPPMAX and GPUs for high-performance computing and parallel computing using clusters like UPPMAX and GPUs for high-performance computing are essential. While not required, experience
-
on air-based cooling systems, they increasingly reach their thermal limits due to rapidly rising power densities in modern CPUs and GPUs. Liquid cooling technologies, such as Direct-to-Chip (D2C) can
-
dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. You will receive extensive training in these techniques as part of your PhD project and will work
-
without reliance on vision. The work will combine auditory perception models, predictive processing and flight control, validated through simulation and experimental flight tests on an embedded GPU platform