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Position Summary Stanford University has made a strategic investment in Marlowe, a GPU‑centric high‑performance computing instrument designed to enable large‑scale, data‑intensive research. The Research Data Scientist will play a critical role in this initiative, leveraging expertise in computational research to develop and optimize workflows and applications that unlock Marlowe’s capabilities. The role requires a deep understanding of computational and data science, machine learning, and the scientific process, as well as 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, contribute to scientific code using machine learning, statistical analysis, and computation, and support a range of disciplines. Additionally, the data scientist will act as a bridge between Marlowe and the broader research community, guiding researchers through technical consultation, training materials, and workshops.
Core Duties 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.
Desired Qualifications Experience supervising technical staff including training, mentoring and coaching. Experience developing and writing grant proposals. Minimum of five years at an Academic Staff – Researcher rank or 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.
Pay Range This role is open to candidates anywhere in the United States. The expected pay range for this position is $142,000 to $200,000 per annum. Stanford University provides pay ranges representing its good‑faith estimate of what the university reasonably expects to pay for a position. The compensation for this position will be based on the location of the successful candidate.
The Cardinal at Work website, https://cardinalatwork.stanford.edu/benefits-rewards, provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
Additional Information Schedule: Full‑time Job Code: 6446 Employee Status: Fixed‑Term Grade: R99 Requisition ID: 105424 Work Arrangement : Hybrid Eligible, Remote Eligible, On Site
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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- English
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