PhD Intern- Computer Science

Pacific Northwest National Laboratory

About The Position

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. We are seeking a PhD intern to contribute to a research compiler that translates ordinary differential equations (ODEs) into chemical reaction networks (CRNs). The project sits at the intersection of compiler construction, applied mathematics, and mathematical chemistry, with the broader goal of enabling computing with chemistry. The intern will work on IR design, transformation passes, and mathematically sound transformations using the MLIR framework. This is a hands-on research role focused on rapid prototyping and correct-by-construction transformations.

Requirements

Candidates must be currently enrolled/matriculated in a PhD program at an accredited college.
Minimum GPA of 3.0 is required.

Nice To Haves

PhD student in Computer Science, Applied Mathematics, Physics, Chemistry or related field.
Strong background in compilers or programming languages (IRs, transformations, SSA).
Interest in dynamical systems or chemical reaction network models.
Solid mathematical maturity (linear algebra, multivariable calculus, ODEs).
Strong C++ programming skills.
Ability to reason about correctness of mathematical transformations.
Experience working with research codebases and prototyping quickly.
Familiarity with MLIR or LLVM (strongly recommended).
Ability to collaborate across CS and mathematical chemistry domains.
Strong communication and documentation skills for research environments.

Responsibilities

contribute to a research compiler that translates ordinary differential equations (ODEs) into chemical reaction networks (CRNs)
work on IR design, transformation passes, and mathematically sound transformations using the MLIR framework
hands-on research role focused on rapid prototyping and correct-by-construction transformations