Pacific Northwest National Laboratory Jobs

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Job Information

Pacific Northwest National Laboratory Post Doctorate RA - Data Science in RICHLAND, Washington

Organization and Job ID

Job ID: 312074

Directorate: Physical & Computational Sciences

Division: Advanced Computing, Mathematics & Data

Group: Data Science & Machine Intelligence

Job Description

The Pacific Northwest National Laboratory (PNNL) seeks a post-doctoral research data scientist with the focus on scientific machine learning. The candidate should have experience with or interest in scientific software development and management of scientific data in accordance with the FAIR principles. The candidate will contribute to the software development, and applied mathematics research in the field of scientific machine learning. The emphasis will be given to modeling and control of heterogenous and large-scale dynamical systems such as those emerging in power system networks, or molecular dynamics simulations. The successful candidate is also expected to help summarize the technical findings and contribute to peer-reviewed publications. The candidate must be adept at collaborating with interdisciplinary technical teams through strong communication and interpersonal skills.

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

  • Strong skills in selected areas of applied mathematics (e.g., analysis, linear algebra, dynamical systems, control theory, graph theory, topology, operator theory).

  • Proficiency in Python language and data science packages (e.g., Numpy, Pandas, SciPy, Matplotlib).

  • Proficiency in modern machine learning libraries (such as Pytorch or Tensorflow)

  • Proficiency with software version control systems (such as Git).

  • Expertise with a broader range of programming languages is a plus (e.g., C/C++, JavaScript)

  • Experience with dynamic visualization of high-dimensional datasets is a plus.

  • Background in basic and applied energy sciences (e.g., computational physics, or computational chemistry, power systems) is a plus.

  • Experience with modern scientific deep learning methods (e.g., Neural ODEs, PINNs, Operator networks, Hamiltonian and Lagrangian neural networks, Graph neural networks) is a plus.

  • Familiarity with constrained optimization tools (e.g. Gurobi, CPLEX) is a plus.

  • Publication record in scientific conferences such as NeurIPS, ICML, ICLR, AAAI is a plus.

Preferred Education/Credential:

PhD degree in Data Science, Computer Science, Applied Mathematics, Computational Physics, Computational Chemistry, Computational Engineering, or related fields

Equal Employment Opportunity

Battelle Memorial Institute (BMI) at Pacific Northwest National Laboratory (PNNL) is an Affirmative Action/Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All BMI staff must be able to demonstrate the legal right to work in the United States. BMI is an E-Verify employer. Learn more at

If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Directorate: Physical & Computational Sci's

Job Category: Post-Graduates and Post-Docs

Group: Artifical Intelligence & Data

Opening Date: 2021-06-07

Closing Date: 2021-06-20