Research Data Scientist
Stanford University
About this position
Position Overview
Stanford University has made a strategic investment in Marlowe, a GPU-centric high-performance computing instrument designed to enable large-scale, data-intensive research. Supporting a wide range of disciplines, Marlowe facilitates sophisticated machine learning applications, including large-language models. The Research Data Scientist will play a critical role in this initiative, leveraging their expertise in computational research to develop and optimize workflows and applications that unlock Marlowe’s capabilities. This role requires a deep understanding of computational and data science, machine learning, and the scientific process. It also demands the ability to leverage high-performance GPU computing to efficiently process and analyze large datasets. The successful candidate will collaborate closely with Stanford faculty and research groups to design, implement, and refine GPU-accelerated data processing pipelines. They will also contribute to scientific codes using machine learning, statistical analysis, and computation to address complex research challenges. Additionally, the data scientist will contribute to the development of novel computational methods ranging from biological data analysis to simulation of physical systems via digital twins. Beyond technical expertise, the Research Data Scientist will act as a bridge between Marlowe and the broader research community. They will guide researchers in adapting their applications to Marlowe’s GPU-powered infrastructure by providing technical consultation, creating training materials, and leading workshops. The ideal candidate will have a strong background in both data science and GPU-centric computational techniques, combined with a passion for fostering collaboration and pushing the boundaries of interdisciplinary research. This position offers an exceptional opportunity to drive transformational research and establish Marlowe as a cornerstone of Stanford’s efforts in pioneering discovery. Remote work for the Research Data Scientist position will be considered. The Research Data Scientist may be asked to attend certain in-person work events during the year regardless of remote status.
Position Description
Code Architecture for GPU Computation Collaborate with Principal Investigators (PIs) and research groups to architect and optimize GPU-accelerated pipelines. Develop innovative computational methodologies Co-author resulting research publications. Algorithm Development and Data Management Design advanced data movement strategies to minimize memory bottlenecks between CPU and GPU, including real-time data streaming methods for scientific applications. Partner with research teams to design novel algorithms and develop high-quality, reusable software to accelerate complex research projects. Research Support and Software Infrastructure Assist PIs in applying for supercomputing resources at national centers once projects are scaled and workloads are appropriate. Offer guidance on maximizing efficiency of large-scale computational experiments. Install, configure, and maintain software stacks for core research functions. Training and Mentorship Design and lead hands-on workshops, and interdisciplinary courses focused on GPU-centric research in fields such as computational biology, NLP and image analysis. Mentor graduate students, postdocs and early-career researchers in computational techniques and research methodologies. Open Science and Research Continuity Integrate open science principles into research workflows, including software for data and computational provenance. Design systems to manage inputs, outputs, and provenance to meet NIH, NSF, and OSTP mandates. Develop tools and workflows to ensure the long-term viability of code and tools used by students and postdocs for future research development. *Other duties as assigned.
Qualifications
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. Education & Experience (Required): 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
Job Location
🔍 Dean of Research, Stanford, California, United States