GPU HPC Intern: DevTech Research & Optimization

NVIDIA; Zürich; Vor Ort; CHF 90.000 - 120.000; Vollzeit

Zusammenfassung

NVIDIA is seeking MSc/PhD students to research and develop GPU-accelerated techniques for high-performance computing, spanning scientific computing, computational engineering, and data science.

You will optimize performance across current and future GPU architectures and collaborate with architecture, research, libraries, and tools teams to shape next-generation platforms and programming models.

Qualifikationen

• Pursuing a MSc or preferably PhD degree in an engineering or computer science related discipline.
• Domain expertise in telecommunications, medical imaging, machine learning, deep learning, or natural sciences is helpful.

Aufgaben

• Research and develop techniques to GPU-accelerate leading applications in HPC fields.
• Perform in-depth analysis and optimization for best performance on current and next-generation GPU architectures.
• Collaborate with architecture, research, libraries, tools, and system software teams to influence design and programming models.

Kenntnisse

C/C++

Fortran

Parallel programming

CUDA/OpenACC

Mathematics

Communication

Ausbildung

MSc or PhD in CS/Engineering

Tools

CUDA

OpenACC

Jobbeschreibung

NVIDIA is seeking MSc/PhD students to research and develop GPU-accelerated techniques for high-performance computing, spanning scientific computing, computational engineering, and data science.

You will optimize performance across current and future GPU architectures and collaborate with architecture, research, libraries, and tools teams to shape next-generation platforms and programming models.