Data Scientist (Nuclear Physics)

You’ll join the Applied Radiation Detection (ARD) Group in the Nuclear, Chemical, and Biological Technologies Division of PNNL’s National Security Directorate. Our group brings together expertise in radiation measurements, novel sensors, advanced detection systems, and data analytics to address national and international security challenges.

• BS/BA in physics, nuclear engineering, computer science, data science, mathematics, or a related technical field and 2 years of relevant experience -OR-
• MS/MA in physics, nuclear engineering, computer science, data science, mathematics, or a related technical field -OR-
• PhD in physics, nuclear engineering, computer science, data science, mathematics, or a related technical field
• Relevant experience includes conducting nuclear physics research or applying nuclear physics principles to scientific or technical problems, along with hands-on experience developing, applying, or evaluating AI or machine learning models using scientific data.
• A PhD in physics, nuclear engineering, computer science, data science, mathematics, or a related field.
• Strong programming skills, particularly in Python; experience with C/C++ is also valuable.
• Strong knowledge in at least one of the following: applied machine learning, agentic AI, deep learning, or statistics.
• Experience building evaluation datasets, test harnesses, agentic harnesses, automated graders, behavioral tests, or analysis pipelines.
• A background in nuclear physics, radiation detection, nuclear measurements, sensor data analysis, or a related scientific field.
• Interest in connecting data-driven methods with physical models and domain knowledge.
• Experience with deterministic NLP, computer vision, retrieval, search, rules, or classical machine-learning methods that complement generative SI.
• A record of clear scientific writing and publication.
• Creativity, strong problem-solving skills, and initiative.
• The ability to contribute to a collaborative, multidisciplinary team.
• Deep expertise in a relevant scientific or technical field, with a desire to grow your capabilities in machine learning and SI.
• Hazardous Working Conditions/Environment
• Not Applicable
• Additional Information
• This position requires the ability to obtain and maintain a federal security clearance.
• A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and co-workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation also examines your foreign connections, drug and alcohol use, foreign influence, and overall conduct.
• U.S. Citizenship
• Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
• Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the applicant selected for hire is subject to pre-employment drug testing, and post-employment random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).
• Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated.
• Testing Designated Position
• This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
• About PNNL
• Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!
• At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.
• Commitment to Excellence and Equal Employment Opportunity
• Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.
• Drug Free Workplace
• If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.
• Security, Credentialing, and Eligibility Requirements
• As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
• BS/BA in physics, nuclear engineering, computer science, data science, mathematics, or a related technical field and 2 years of relevant experience -OR-
• MS/MA in physics, nuclear engineering, computer science, data science, mathematics, or a related technical field -OR-
• PhD in physics, nuclear engineering, computer science, data science, mathematics, or a related technical field
• Relevant experience includes conducting nuclear physics research or applying nuclear physics principles to scientific or technical problems, along with hands-on experience developing, applying, or evaluating AI or machine learning models using scientific data.
• A PhD in physics, nuclear engineering, computer science, data science, mathematics, or a related field.
• Strong programming skills, particularly in Python; experience with C/C++ is also valuable.
• Strong knowledge in at least one of the following: applied machine learning, agentic AI, deep learning, or statistics.
• Experience building evaluation datasets, test harnesses, agentic harnesses, automated graders, behavioral tests, or analysis pipelines.
• A background in nuclear physics, radiation detection, nuclear measurements, sensor data analysis, or a related scientific field.
• Interest in connecting data-driven methods with physical models and domain knowledge.
• Experience with deterministic NLP, computer vision, retrieval, search, rules, or classical machine-learning methods that complement generative SI.
• A record of clear scientific writing and publication.
• Creativity, strong problem-solving skills, and initiative.
• The ability to contribute to a collaborative, multidisciplinary team.
• Deep expertise in a relevant scientific or technical field, with a desire to grow your capabilities in machine learning and SI.