Postdoctoral Research Associate - HPC System Architecture and Intelligent Storage Design
Oak Ridge National Laboratory
Requisition Id16766 Overview: The National Center for Computational Sciences (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral research associate in High-Performance Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems in the world. This position is in the Technology Integration group within NCCS. Specific areas of research interest include: Telemetry collection and analysis to inform system optimization, workload characterization, and predictive fault tolerance in HPC systems. Architectural exploration and performance modeling of high-bandwidth memory (HBM) and DDR memory systems in the context of data-intensive scientific computing. Redesign of storage systems to meet evolving demands in AI/ML and edge-to-HPC workflows, including support for data movement, retention policies, and user-defined storage behaviors. Major Duties and Responsibilities: Collaborate with internal and external researchers on a variety of data and storage-related research projects for use cases in HPC, scientific AI, and scientific edge computing. Conduct I/O and storage performance characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Collect, analyze, and leverage telemetry data from HPC systems to support data-driven design decisions and performance tuning. Explore trade-offs in DDR and HBM usage patterns, and propose architectural improvements for mixed-memory and bandwidth-intensive workloads. Design and evaluation of ephemeral, user-configurable, and composable data and storage systems. Design system-level approaches for time-sensitive or data-intensive processing of data originating at scientific edge systems using large-scale HPC/AI computational and storage systems. Coauthor peer-reviewed publications, technical reports, and presentations. Seek membership and service opportunities in professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant area with an education and a research track record in HPC/AI/edge systems and storage research within pastfiveyears. Preferred Qualifications: Ability to work independently to design and deploy methods at scale. Familiarity with hardware-software co-design, memory hierarchies (DDR, HBM), and system-level telemetry tools. Experience in HPC and associated software development for applications, middleware, and/or system software. Flexibility to adapt to diverse R&D projects and tasks. Effective communicator in both verbal and written forms. Ability to collaborate with scientists, engineers, and sponsors. Interest in mentoring student internships. Applicants cannot have received their PhD more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding. Special Requirements: HSPD-12 PIV badge: This position requires the ability to obtain and maintain an HSPD-12 PIV badge. 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. If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email:View email address on click.appcast.io. 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 View email address on click.appcast.io. 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. Oak Ridge National Laboratory
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