Post Doctorate Research Associate- Complex Data Models

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 National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex, real-world threats to our nation and the world. 

The AI and Data Analytics Division, part of the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support. 

Responsibilities
Responsibilities include: 

• Develop and use mathematics and machine learning approaches to address research challenges in national security.
• Ability to combine mathematics, e.g., computational topology, representation theory, geometry, applied category theory, graph and hypergraph theory, with machine learning to solve challenging problems including the analysis of both traditional complex systems and AI-based systems.
• Ability to combine mathematics including computational topology, applied category theory, graph and hypergraph theory, and related techniques with machine learning as appropriate to produce methods for analyzing complex data systems (e.g., knowledge graphs, semantic databases, authorization systems).
• Convey impactful research results in technical documents, verbally, and in presentation form to diverse audiences with varied technical backgrounds.

This posting is hiring for multiple positions and the location for each position will be decided based on project needs and requirements at the time of hire.

Qualifications

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:

• Degree in Mathematics or Computer Science or related field.
• Strong mathematical background and prior publications using techniques from topology, algebra, geometry, or category theory.
• Experience programming in Python.
• Experience working with knowledge graphs and other complex systems data.
• Experience in the science of deep learning or mechanistic interpretability.