Postdoctoral Research Associate - Programming Systems for Extreme Heterogeneity

Oak Ridge National Laboratory • Oak Ridge, TN

78d • Onsite

About The Position

The Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking an exceptional Postdoctoral Researcher to advance programming systems for extreme-scale, heterogeneous computing. This role sits at the intersection of compiler infrastructure, formal verification, runtime systems, and hardware/software co‑design—expanding into emerging paradigms such as quantum and analog computational models. You will explore how compilers, runtimes, and AI-driven agents can co-optimize complex architectures, reasoning across conventional processors (CPUs/GPUs), custom accelerators, and next-generation quantum and analog devices. Your work will contribute to a vision of autonomous system engineering in which AI agents understand algorithmic intent, architectural constraints, and performance models—driving system co-design across the entire computing stack.

Requirements

• Ph.D. in Computer Science, Computer Engineering, or a closely related field.
• Strong experience with LLVM (e.g., writing passes, IR transformations) and HPC programming in C++, MPI, OpenMP, CUDA, or related models.
• Solid understanding of distributed-memory systems and many‑core architectures.
• Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment.

Nice To Haves

• Experience with automated reasoning or verification tools (e.g., Z3, TLA+, LEAN) to ensure correctness of compiler- or AI‑generated code.
• Background in linear algebra, graph algorithms, and related areas central to dataflow and tensor optimization.
• Familiarity with architectural simulators (e.g., Gem5, SST) or HDLs.
• Exposure to quantum programming models (e.g., QIR, Q#, Qiskit, Cirq) or analog/neuromorphic systems; interest in integrating these paradigms into unified compilation and optimization strategies.
• Experience with Julia, Rust, Python, Kokkos, OpenSHMEM, or similar emerging ecosystem tools.

Responsibilities

• Advance the LLVM toolchain to support autonomous “closed-loop” optimization environments, enabling AI agents to analyze, transform, and validate IR with performance-driven reasoning.
• Investigate methods through which AI agents guide architectural design decisions for massively parallel heterogeneous systems, including pathways that integrate quantum or analog co-processors.
• Profile, model, and optimize distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints.
• Explore how compilers and runtimes can unify classical, quantum, and analog execution models under a shared optimization framework.

Benefits

• medical and retirement plans
• flexible work hours
• on-site fitness
• banking
• cafeteria facilities
• 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
• Employee Discounts

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree