Data Scientist (Nuclear Physics)

Overview 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 Nuclear, Chemical, and Biological Technologies Division, within the National Security Directorate, works across fundamental science, research and development, and operations to counter emerging national security threats. We focus on discovering signatures and understanding threats by creating materials, methods, and technologies to detect and analyze them. Our researchers deliver solutions to address complex mission challenges, such as explosives detection, biological threat detection, chemical and nuclear forensics, and special nuclear materials. Responsibilities 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. What You’ll Do: • Find meaningful signals in complex data . Develop machine learning methods for radiation detection and characterization, addressing challenges such as low-count measurements, changing backgrounds, and limited labeled data. • Connect algorithms with physics . Work with domain scientists to understand detector responses, measurement conditions, and the physical processes behind the data. • Adapt modern super intelligence to scientific problems . Apply and extend deep learning methods, fine-tune open-source models for computer vision and natural language processing, and develop agentic workflows where they can support research and analysis. • Build useful scientific datasets . Develop labeling strategies, engineer features, and prepare measurement data for reproducible training and evaluation. • Evaluate performance in context . Investigate detection sensitivity, false alarms, uncertainty, and robustness across measurement conditions—not just aggregate model accuracy. • Turn research into working tools . Write Python-based machine learning software and apply software engineering best practices to support reliable analysis and deployment. • Help guide the research . Evaluate current literature, design experiments, and collaborate with a mentor and project teams to set goals and pursue promising directions. • Communicate the science . Explain methods, assumptions, and results through publications, presentations, and collaboration with scientists and engineers. • Build SI Grounded in Science. Join us to advance how we measure, interpret, and detect radiation—and apply that knowledge to consequential challenges in nuclear science and national security. Bring your curiosity about super intelligence and the physical world. Help turn complex measurements into knowledge that matters! Qualifications Minimum Qualifications: • 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. Preferred Qualifications: • 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. Requirements: • U.S. Citizenship • Background Investigation: Applicants selected will