Research - HPC Neuromorphic Systems

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As a research staff member, you will conduct and lead research at the intersection of high performance computing, artificial intelligence, and neuromorphic computing. You will develop scalable algorithms, software, and AI-enabled methods for modeling, simulating, and co-designing spiking neural networks and emerging computing systems. Drawing on expertise in distributed computing, machine learning, and architecture search, you will use leadership-class and exascale systems to evaluate and optimize new approaches.

You will collaborate across disciplines, help establish new research directions, contribute to competitive proposals, mentor students and early-career researchers, and communicate results through peer-reviewed publications and presentations.

The Learning Systems Group at Oak Ridge National Laboratory advances the next generation of artificial intelligence by co-designing algorithms and computing systems to address complex challenges in science, energy, national security, and health. Our researchers develop scalable machine-learning models, deep-learning architectures, and data-driven methods for platforms ranging from edge sensors and neuromorphic systems to national supercomputers and quantum computers. Our work includes scientific knowledge discovery, autonomous and energy-efficient systems, threat intelligence and data fusion, agent-based modeling and digital twins, and predictive analysis for environmental and health applications.

We are committed to recruiting and retaining highly motivated, creative research staff members and students who will help develop intelligent systems that learn, reason, and operate effectively across diverse computing environments.

• Conduct and lead original research in scalable algorithms and software for modeling, simulating, and optimizing spiking neural networks and neuromorphic systems.
• Develop AI-driven architecture search and hardware-software co-design methods for neuromorphic systems, including evolutionary and differentiable approaches where appropriate.
• Design, implement, optimize, and evaluate distributed training, inference, and simulation workflows on GPU-accelerated leadership-class and exascale computing systems.
• Develop methods for automating large-scale modeling and simulation campaigns, including agentic AI and scientific workflow orchestration where appropriate.
• Characterize performance, scalability, portability, reliability, data movement, and power consumption under load across heterogeneous computing platforms.
• Develop and maintain high-quality research software, including documentation, testing, reproducible workflows, and collaborative version control.
• Build strong collaborations within ORNL and across the high performance computing, artificial intelligence, and neuromorphic computing communities; contribute to proposals, project plans, milestones, and sponsor deliverables; and mentor students and early-career researchers.
• Publish research in peer-reviewed journals and conferences, author technical reports, and represent ORNL and the Learning Systems Group through presentations at conferences, workshops, and invited forums.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

• Ph.D. in Data Science and Engineering, Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a closely related field.
• Strong programming proficiency in Python and C or…