Stanford University is seeking a Research Data Scientist to support the Marlowe initiative, a GPU-centric high-performance computing instrument designed to enable large-scale, data-intensive research, and to collaborate with faculty and research groups to design, implement, and refine GPU-accelerated data processing pipelines.
Requirements
- Ph.D. in a computational or data-intensive related field or equivalent
- Comfortable running and troubleshooting jobs in a batch scheduled environment
- Considerable experience with Linux
- Experience with GPU-centric computational techniques
- Strong background in data science and machine learning
- Experience with high-performance computing and large-scale data analysis
- Experience with programming languages such as Python, C++, or Java
Responsibilities
- Collaborate with Principal Investigators (PIs) and research groups to architect and optimize GPU-accelerated pipelines
- Develop innovative computational methodologies
- Co-author resulting research publications
- Design advanced data movement strategies to minimize memory bottlenecks between CPU and GPU
- Partner with research teams to design novel algorithms and develop high-quality, reusable software to accelerate complex research projects
- Assist PIs in applying for supercomputing resources at national centers once projects are scaled and workloads are appropriate
- Install, configure, and maintain software stacks for core research functions
Other
- Experience supervising technical staff including training, mentoring and coaching
- Experience developing and writing grant proposals
- A minimum of five years at an Academic Staff - Researcher rank or have equivalent experience
- Extensive publication list including first author publications
- Ability to work in a team environment and collaborate with researchers and staff
