Stanford University
Overview
Research Data Scientist — Dean of Research, Stanford, California, United States. This is a 3-year fixed term appointment. Stanford Data Science (SDS) is a dynamic and growing unit within the VP/Dean of Research. SDS advances data science and its application across the campus, spanning seven schools with faculty, post-doctoral fellows, PhD students, staff, and administrators. The staff support the organization’s goals and enable faculty and students to conduct cutting-edge research and innovation in data-driven learning, tools, and methods for a data-intensive future. Position Summary Stanford University has invested in Marlowe, a GPU-centric high-performance computing instrument designed for 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. This role requires a deep understanding of computational and data science, machine learning, and the scientific process, and the ability to leverage high-performance GPU computing to efficiently process and analyze large datasets. The successful candidate will collaborate with Stanford faculty and research groups to design, implement, and refine GPU-accelerated data processing pipelines, contribute to scientific codes using machine learning, statistical analysis, and computation, and develop novel computational methods ranging from biological data analysis to digital-twin simulations. The candidate will also act as a bridge between Marlowe and the broader research community, providing technical consultation, training materials, and workshops. Remote work will be considered; some in-person events may be required during the year. 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 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 national supercomputing resources when projects scale and workloads require it. Provide 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 areas 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 long-term viability of code and tools used by students and postdocs for future research development.
Desired 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 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 scheduling environment. Considerable experience with Linux. Pay Range This role is open to candidates anywhere in the United States. Stanford University has five Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range is $142,000 to $200,000 per year. Stanford provides a pay ranges and benefits overview; specifics will be discussed during the hiring process. The job duties listed are typical examples and may vary by department or program needs. Stanford will provide reasonable accommodations to applicants and employees with disabilities. Stanford is an equal employment opportunity and affirmative action employer. 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
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Research Data Scientist — Dean of Research, Stanford, California, United States. This is a 3-year fixed term appointment. Stanford Data Science (SDS) is a dynamic and growing unit within the VP/Dean of Research. SDS advances data science and its application across the campus, spanning seven schools with faculty, post-doctoral fellows, PhD students, staff, and administrators. The staff support the organization’s goals and enable faculty and students to conduct cutting-edge research and innovation in data-driven learning, tools, and methods for a data-intensive future. Position Summary Stanford University has invested in Marlowe, a GPU-centric high-performance computing instrument designed for 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. This role requires a deep understanding of computational and data science, machine learning, and the scientific process, and the ability to leverage high-performance GPU computing to efficiently process and analyze large datasets. The successful candidate will collaborate with Stanford faculty and research groups to design, implement, and refine GPU-accelerated data processing pipelines, contribute to scientific codes using machine learning, statistical analysis, and computation, and develop novel computational methods ranging from biological data analysis to digital-twin simulations. The candidate will also act as a bridge between Marlowe and the broader research community, providing technical consultation, training materials, and workshops. Remote work will be considered; some in-person events may be required during the year. 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 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 national supercomputing resources when projects scale and workloads require it. Provide 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 areas 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 long-term viability of code and tools used by students and postdocs for future research development.
Desired 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 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 scheduling environment. Considerable experience with Linux. Pay Range This role is open to candidates anywhere in the United States. Stanford University has five Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range is $142,000 to $200,000 per year. Stanford provides a pay ranges and benefits overview; specifics will be discussed during the hiring process. The job duties listed are typical examples and may vary by department or program needs. Stanford will provide reasonable accommodations to applicants and employees with disabilities. Stanford is an equal employment opportunity and affirmative action employer. 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
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