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Pacific Northwest National Laboratory PhD Intern - Integrated Waste Management System Analysis in RICHLAND, Washington

Organization and Job ID

Job ID: 311907

Directorate: Energy and Environment

Division: Earth Systems Science

Group: Operational Systems

Job Description

Join a dynamic team of scientists and engineers focused on advancing numerical techniques and algorithms to analyze, understand and predict the nuclear fuel cycle system. Pacific Northwest National Laboratory (PNNL) is developing modeling tools for the integrated system analysis of the waste management system and is focusing on spent fuel and high-level radioactive waste that would be generated by advanced nuclear reactors.PNNL is pursuing the linkage of the more detailed waste management system analysis tools with broader CYCLUS nuclear fuel cycle codes.

The Operational Systems Engineering Group within the Earth Systems Science Division at PNNL seeks applications for a PhD Intern position. The applicant must have experience with the use of the CYCLUS nuclear fuel cycle code and an understanding of the back-end of the nuclear fuel cycle.

Through their work, the candidate will also develop an internal and external network of collaborators and project partners and participate in professional societies at the regional and national level. The candidate is expected to publish scientific findings in high-impact peer-reviewed journals as well as present work at professional conferences. Finally, the position requires that the candidate complies with PNNL policies regarding environmental health, safety, and protection of intellectual property. The position is immediately available for 24 months, with the potential to transition to a permanent position, dependent upon available funding and sustained performance.

Minimum Qualifications

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

Preferred Qualifications

An ideal candidate will have a demonstrated commitment to data quality and accuracy, strong written and oral communication skills as evidenced by scientific publications and conference presentations and be able to work independently and in a team setting.

The applicant should have a significant level of knowledge and/or direct working experience in nuclear energy, with familiarity and experience with the back-end of the nuclear fuel cycle. Demonstrated experience in one or more of the following is preferred:

  • Experience with nuclear system analysis

  • Understanding of advanced nuclear reactor concepts

  • Experience and understanding of the back-end of the nuclear fuel cycle

  • Experience using the Cyclus fuel cycle system analysis code

  • Experience with artificial intelligence and machine learning

  • Proficiency in Python with a working knowledge of git and software QA/QC

  • Degree in Mechanical Engineering, Chemical Engineering, Nuclear Engineering or related fields with relevant experience.

  • 3.25 GPA or higher is preferred

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 jobs.pnnl.gov.

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 https://jobs.pnnl.gov/help.stm

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.

Other Information

All remote modeling; no lab or field work

Directorate: Energy & Environment

Job Category: Master's and PhD Level Internships

Group: Operational Syst Engineering

Opening Date: 2021-04-05

Closing Date: 2021-04-20

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