Post Doctorate Research Associate - Hardware Design Methodologies

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Integrated Discovery Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The Integrated Discovery Sciences Directorate (IDSD) leads fundamental research across biology, chemistry, earth and environmental sciences, materials science, advanced computing, artificial intelligence, quantum information science, mathematics, autonomy, and DOE national user facilities. Our vision is to accelerate scientific discovery by observing, understanding, simulating, predicting, and controlling dynamic biotic-abiotic processes and interactions within complex biological, chemical, material, and Earth systems. We intentionally connect disciplines to advance fundamental discovery science, develop transformative scientific capabilities, and address the nation's most important challenges in energy, environmental resilience, biotechnology, advanced manufacturing, health, and national security.

The Pacific Northwest National Laboratory (PNNL) Future Computing Technology Group is seeking exceptional Post-Doctoral Research Associates to advance research in next-generation electronic design automation (EDA), specialized computing systems, and hardware prototyping. As the complexity of computing systems continues to increase, new methodologies are required to dramatically improve the productivity, automation, and accessibility of hardware design. Our team is developing innovative approaches that span the entire hardware design lifecycle, from high-level programming models and compiler technologies to high-level synthesis (HLS), architecture exploration, register-transfer level (RTL) generation, physical implementation, prototyping, and experimental validation.

This position offers a unique opportunity to work at the intersection of compilers, high-level synthesis, computer architecture, artificial intelligence (AI) for hardware design, and semiconductor prototyping. The successful candidate will contribute to research on advanced HLS capabilities, compiler-driven hardware generation, automated design-space exploration, and methodologies for translating high-level application descriptions into efficient hardware implementations.

Research may span open-source and commercial design ecosystems and include field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) targets, heterogeneous and domain-specific accelerators, chiplet-based systems, and emerging computing architectures. A major objective is to develop scalable, reproducible, and increasingly automated methodologies capable of moving from application and architectural specifications through hardware implementation, prototyping, and eventual silicon realization.

As a member of our collaborative and multidisciplinary team, the successful candidate will work with researchers in computer architecture, compilers, EDA, AI, semiconductor technologies, and scientific application domains. The position provides access to advanced computational resources, semiconductor design tools, prototyping platforms, electronics laboratory facilities and opportunities to participate in hardware fabrication and experimental validation activities. It also provides substantial opportunities to publish at premier conferences and journals and contribute to open-source research software.

• Develop novel and scalable methodologies for electronic design automation, high-level synthesis, and hardware/software co-design.
• Develop compiler and intermediate-representation technologies for translating high-level applications and computational models into optimized hardware implementations.
• Investigate AI-assisted and autonomous hardware design methodologies, including automated design-space exploration, optimization,…