Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
publications at top-tier venues such as CVPR, ICCV, ECCV, NeurIPS or ICRA. You will have access to extensive compute resources at TU Delft, ranging from local GPU servers to large-scale HPC infrastructure
-
-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
-
. Skilled in MATLAB and Python. Experience with C++ and GPU programming (CUDA) is an advantage. Ability to work in a team, communicate effectively, coordinate multidisciplinary collaborations, and manage
-
research profile, and an international network around big data in marine sciences. The candidate will have access to NIOZ’s high-performance computing cluster, GPU nodes for deep learning, dedicated data
-
Microscopy Center. The project further benefits from excellent dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. This is a full-time, two-year
-
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
-
of computing systems—driven by edge devices, AI accelerators, and domain-specific architectures—has created unprecedented hardware heterogeneity. Modern platforms combine CPUs, GPUs, FPGAs, ASICs, and emerging
-
resources of TU Delft, ranging from personal machines, to shared GPU servers, the Delft AI Cluster that is shared across departments, as well as DelftBlue , which is one of the top 250 supercomputers in