Senior Research Scientist Advanced Computing Systems

Senior Research Scientist Advanced Computing Systems

The Advanced Technologies Section (ATS) at Oak Ridge National Laboratory is seeking a highly motivated and experienced Senior Research Scientist to provide scientific and technical leadership in systems architecture for next-generation leadership-class high-performance computing. This position is embedded within the Oak Ridge Leadership Computing Facility (OLCF) and serves as a strategic research leader at the intersection of advanced computing systems, storage architectures, and high-performance networking.

The successful candidate will lead collaborations with other research staff and postdoctoral researchers in developing and evaluating transformative technologies for future leadership computing systems. This position is part of the Advanced Technologies Section within the National Center for Computational Sciences (NCCS) Division.

Major

Duties and Responsibilities:

• Lead and grow a multidisciplinary team of research scientists and postdoctoral researchers focused on next-generation HPC systems architecture, providing mentorship, technical direction, and career development guidance.
• Define and execute a strategic research agenda in advanced computing systems architecture, with emphasis on hybrid classical-quantum computing systems, next-generation high-performance interconnects, and future storage technologies for leadership-scale workloads.
• Architect and evaluate hybrid HPC-quantum computing systems, including co-design of system integration frameworks, communication substrates, and programming models that bridge classical and quantum computational resources.
• Lead research and development efforts in next-generation interconnect technologies, including evaluation of emerging fabric architectures, topology design, routing strategies, and in-network computing capabilities for exascale and post-exascale systems.
• Drive research into next-generation storage systems and hierarchies, including storage-class memory, disaggregated storage architectures, high-bandwidth parallel file systems, and data movement strategies at leadership scale.
• Lead collaborations with internal ORNL teams, DOE program offices, national laboratory partners, and industry and academic collaborators on advanced computing systems projects.
• Represent the OLCF and ATS in high-visibility technical forums, standards bodies, and vendor co-design engagements relevant to future leadership computing system acquisition.
• Author and contribute to peer-reviewed publications, technical reports, and research proposals; secure external funding to sustain and grow the group's research portfolio.
• Evaluate and evolve state-of-the-art design processes and system characterization methodologies used at leadership computing facilities and disseminate findings and best practices to the broader HPC community.

Basic Qualifications:

• PhD. in computer science, computer engineering, electrical engineering, computational science, or a closely related field.
• 8 or more years of relevant research experience beyond the Ph.D., with a demonstrated record of independent research accomplishment in HPC systems, computer architecture, or a closely related domain.
• Demonstrated experience leading or co-leading research teams, including supervision of staff researchers, postdoctoral associates, or graduate students.

Preferred Qualifications:

• Proven experience in HPC systems architecture, including large-scale system design, integration, and characterization at leadership computing facilities.
• Research experience with hybrid classical-quantum computing systems, including familiarity with quantum hardware platforms, quantum-classical interfaces, or co-design of hybrid algorithms and system software stacks.
• Deep technical knowledge of high-performance interconnect technologies, including emerging fabric architectures (e.g., high-radix topologies, CXL, UCIe, or comparable), routing, and in-network computing.
• Expertise in advanced storage systems for HPC, including parallel file systems, storage-class memory, disaggregated and composable storage, and high-performance I/O frameworks.
• Experience with heterogeneous node and system…