Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Princeton University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- National University of Singapore
- FCiências.ID
- Humboldt-Universität zu Berlin
- Lawrence Berkeley National Laboratory
- Nanyang Technological University
- University of Arkansas
- University of Idaho
- University of Minho
- University of Oslo
- Université Catholique de Louvain (UCL)
- 2 more »
- « less
-
Field
-
. Key attractions are access to a high-performance computing cluster (GPU/CPU and more than 300TB of data), two 3T Prisma MR scanners, and an MR compatible digital EEG system as well as collaboration
-
these codes in C++ or Fortran Adopting these codes for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in
-
GPU clusters to enhance efficiency and scalability. Knowledge, Skills, and Abilities: Good communication and teamwork skills; Strong skill in large language model customization techniques including
-
development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
-
vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D projects Key Competencies Able to build and maintain strong working relationships with
-
recent architectures such as vision transformer or foundation models Experience in working with subsurface imaging Proficiency in leveraging GPUs and distributed training for large-scale datasets is highly
-
(LLMs); Configure and optimize cloud computing solutions or on-premise infrastructures that ensure high availability and scalability; Implement tools for efficient resource management, such as GPU