PhD Research Intern: Graph ML for Science & Energy

Wayne State University; Richland (WA); On-site; USD 22,000 - 36,000; Full time

Job summary

Pacific Northwest National Laboratory (PNNL) invites PhD‑level interns to join the Advanced Computing, Mathematics, and Data Division (ACMDD) to explore graph neural networks and scientific machine learning with applications in electronic design automation.

The role emphasizes designing and implementing graph‑focused models, collaborating across disciplines, and communicating findings for potential publication. Strong Python, ML library experience, and a track record of research are desirable.

Qualifications

• Candidates must be currently enrolled/matriculated in a PhD program.
• Minimum GPA of 3.0 is required.
• Strong skills in graph models, graph representation learning, and ML for science.

Responsibilities

• Focus on foundational graph models, graph representation learning, and graph neural networks.
• Develop scientific software and manage scientific data following FAIR principles.
• Help summarize technical findings and contribute to peer‑reviewed publications.

Skills

Graph neural nets

Python

Machine learning

Communication

Education

PhD candidate in a relevant field

GPA 3.0 or higher

Tools

Git

PyTorch

TensorFlow

Numpy

Pandas

SciPy

Matplotlib

Job description

Pacific Northwest National Laboratory (PNNL) invites PhD‑level interns to join the Advanced Computing, Mathematics, and Data Division (ACMDD) to explore graph neural networks and scientific machine learning with applications in electronic design automation.

The role emphasizes designing and implementing graph‑focused models, collaborating across disciplines, and communicating findings for potential publication. Strong Python, ML library experience, and a track record of research are desirable.