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, Earth and Biological Sciences, Physical and Computational 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 Physical and Computational Sciences Directorate's (PCSD’s) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. But our most important resource is our people—experts across the range of scientific disciplines who team together to take on the biggest scientific challenges of our time.  

The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing artificial intelligence, applied mathematics, computing technologies, and data and computational engineering. Our scientists and engineers apply end-to-end co-design principles to advance future energy-efficient computing systems and design the next generation of algorithms to analyze, model, understand, and control the behavior of complex systems in science, energy, and national security. 

Responsibilities

Join the Future Computing Technology Group at Pacific Northwest National Laboratory and help shape the next wave of computing innovation. We are looking for an outstanding Post-Doctoral Research Associate who is passionate about pushing beyond the limits of traditional architectures and developing hardware and design methodologies that will power the scientific breakthroughs of tomorrow.

As computational demands rapidly evolve, our team is pioneering neuromorphic and nature-inspired approaches to overcome bottlenecks in performance, efficiency, and edge intelligence. This is an opportunity to work on bold, forward-leaning research that redefines how future systems are designed and built.

What You’ll Do

In this role, you will work at the dynamic intersection of hardware design, EDA, and emerging computing architectures, contributing to research efforts that span concept to deployment. You will:

• Develop novel, scalable methodologies for electronic design automation (EDA).
• Co-design cutting-edge neuromorphic and nature-inspired hardware architectures for scientific computing and edge inference.
• Advance new techniques and tools that integrate hardware, compilers, and runtime systems.
• Collaborate with top scientists across computer architecture, materials science, and applied research domains.
• Contribute to high-impact publications and present your work at leading conferences.
   

Minimum Qualifications:

• Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.

Preferred Qualifications:

• Demonstrated experience with advanced hardware synthesis methodologies, including creating or optimizing flows for emerging architectures.
• Proficiency with modern compiler frameworks such as LLVM or MLIR, with the ability to contribute to front-end, mid-level, or backend transformations.
• Strong working knowledge of hardware design languages (e.g., Verilog, VHDL, SystemVerilog) and associated design, simulation, and verification tools.
• Hands-on experience with physical design, layout, and tape-out processes, using both commercial EDA tools and open-source toolchains.
• Experience collaborating across hardware–software co-design efforts or contributing to full-stack architecture research is a plus.