Requisition Id 16771
Overview:
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. The ATS is an applied research and development organization that provides scientific, technical, and thought leadership for the deployment of compute- and data-intensive computing environments, partnering closely with system vendors, national laboratories, and the broader HPC research community to shape the trajectory of leadership computing.
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 architectures, including accelerator-based computing and associated programming models.
- Experience collaborating with system vendors on co-design of hardware and software for future HPC platforms.
- Excellent interpersonal, oral, and written communication skills, with experience representing research programs to leadership, sponsors, and the broader scientific community.
- Strong personal motivation and the ability to thrive in a fast-paced, mission-driven applied research environment.
Security, Credentialing, and Eligibility Requirements:
For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.
To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
About ORNL:
As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.
ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.
Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.
This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.
If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.
ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The emergence of Senior Research Scientists specializing in Advanced Computing Systems represents a critical pivot in the leadership-class high-performance computing sector from homogenous acceleration to heterogeneous, post-exascale system co-design. As the quantum and advanced computing ecosystems mature, the structural necessity for roles that bridge physical hardware architectures and systems software stacks becomes paramount to resolving the integration bottleneck between classical accelerators and emerging quantum coprocessors. This role type serves as a high-leverage stabilization point within the infrastructure enablement layer, ensuring that next-generation high-performance fabrics, storage hierarchies, and programming models are architecturally compatible with exascale-and-beyond workloads. Market signals from major technology consortia and national computing infrastructure strategies highlight that such expertise is essential for mitigating the systemic risks of architectural stagnation in high-compute industries. By converting complex physical and algorithmic breakthroughs into deterministic computing platforms, this function secures the foundation for long-term scientific readiness and competitive differentiation in the global deep-tech value chain.
The leadership-class computing landscape is undergoing a decisive shift from laboratory-scale heterogeneous systems to the integration of high-fidelity computational kernels within global high-performance computing ecosystems. While hardware development continues to progress across diverse accelerator modalities, the primary bottleneck for industrial and scientific adoption has shifted to the systems architecture layer, specifically regarding the reproducibility and scalability of hybrid classical-quantum computing workflows. The current industry focus lies on bridging classical and quantum capabilities at scale, necessitating a sophisticated management of the software-hardware interface to ensure that hybrid topologies can handle the data throughput requirements of massive high-performance computing installations.
Workforce scarcity is particularly acute at the intersection of domain-specific industrial variables and advanced systems engineering. As organizations move beyond standard exascale benchmarks, the ecosystem requires specialized architects who can navigate the fragmentation of emerging fabric stacks and the lack of standardized benchmarking protocols for post-exascale platforms. Current sector dynamics, influenced by public-private funding cycles and national technology strategies, place a premium on roles that can drive interoperability across disparate accelerated and disaggregated storage platforms. This structural layer of expertise is the primary mechanism for maintaining momentum as the technology transitions through varying Technology Readiness Levels (TRLs).
Integration with existing high-performance computing environments remains a high-risk dependency for the sector. The evolution of the value chain depends on the ability to translate complex materials science, fluid dynamics, and quantum optimization problems into hardware-native formulations without disrupting established leadership computing facility operational frameworks. Consequently, the availability of senior researchers capable of orchestrating these complex cross-functional dependencies is a primary determinant of whether a facility can successfully transition from traditional petascale and exascale processing to true accelerated hybrid deployment.
The capability architecture for this role type centers on the synchronization of advanced systems co-design with the protocols of enterprise-grade high-performance engineering. Mastery of the hardware-agnostic software layer and systems programming models is essential for ensuring that simulations and workflows are optimized for the specific constraints of current accelerated processors, high-radix fabric topologies, and disaggregated storage hierarchies. This requires a deep understanding of the integration points between high-level runtime systems and the underlying hardware description substrates that manage hybrid classical-quantum executions.
These capabilities are fundamental to the throughput of leadership computing facilities, as they enable the parallelization of architecture research initiatives alongside the development of scalable cloud and storage infrastructures. By establishing rigorous verification, validation, and architectural simulation frameworks, this function provides the leverage needed to assess the true value of next-generation hardware before full-scale capital allocation. Furthermore, the ability to manage complex stakeholder landscapes ensures that scientific outputs are reconciled with the practical constraints of multi-institutional collaboration and data sovereignty. Such expertise reduces the iteration friction between abstract hardware research and product delivery, which is critical for long-term interoperability within the emerging advanced-computing-as-a-service market. - Accelerates the deterministic transition from theoretical computing research to leadership-class system deployment
- Mitigates systemic execution risks by synchronizing long-term architecture research with near-term hardware roadmaps
- Facilitates the integration of emerging quantum computational kernels into standardized high-performance computing infrastructures
- Strengthens the reliability of organizational technology strategies through the implementation of rigorous fabric benchmarking
- Reduces iteration friction between fundamental hardware breakthroughs and the deployment of scalable systems software
- Optimizes the allocation of specialized technical talent across research, development, and strategic vendor portfolios
- Enhances the stability of the advanced computing value chain by providing predictable requirement frameworks for external partners
- Supports the scaling of simulation capabilities by managing the complex dependencies of hybrid quantum-classical networks
- Improves the transparency of technology readiness level progression for stakeholders in the scientific and public sectors
- Enables the structural reproducibility of large-scale computational experiments through the standardization of implementation protocols
- Protects high-capital research and development investments by ensuring alignment between system co-design and commercial scalability
- Orchestrates the convergence of academic research pathways with the practical demands of global leadership-ready facilitiesIndustry Tags: High-Performance Computing, Systems Architecture, Post-Exascale Co-Design, Hybrid Classical-Quantum, Fabric Interconnects, Disaggregated Storage, Technology Translation, Deep Tech Strategy, Algorithmic Benchmarking
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