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Nuclear Engineering Data Scientist
- Lynchburg, Virginia, United States
- Lynchburg, Virginia, United States
About
Develop and deploy machine learning models, including deep neural networks, convolutional neural networks, and Bayesian neural networks, to solve nuclear engineering problems. Design hybrid modeling frameworks that combine physics‑based and data‑driven approaches for applications such as critical heat flux prediction and reactor physics simulations. Implement uncertainty quantification techniques, such as ensembling and Bayesian methods, to ensure robust and reliable predictions in nuclear systems. Optimize nuclear engineering processes using advanced AI methodologies, including transfer learning and generative models. Collaborate with cross‑functional teams to integrate ML models into existing nuclear engineering tools. Lead efforts in data augmentation, synthetic data generation, and domain adaptation to enhance model performance in data‑scarce scenarios.
Required Qualifications
A minimum of a bachelor’s degree in Nuclear Engineering, Computer Science, or a related field, with a strong focus on machine learning and artificial intelligence. A minimum of ten (10) years of relevant experience. Proven expertise in deep learning frameworks such as TensorFlow and PyTorch. Proficiency in programming languages and tools, including Python, C++, and MATLAB. Experience with nuclear codes such as MCNP, Serpent, OpenMC, and CTF. Demonstrated ability to develop and validate hybrid modeling techniques in nuclear engineering contexts. Familiarity with uncertainty quantification methods and transfer learning techniques. Strong publication record in reputable journals and conferences, showcasing contributions to AI and nuclear engineering. Excellent communication skills and ability to present complex technical concepts to diverse audiences. U.S. citizenship and ability to obtain and maintain a DOE or DOD security clearance as required.
Preferred Qualifications
Ph.D. or M.Sc. in Nuclear Engineering, Computer Science, or a related field. Strong publication record in reputable journals and conferences, showcasing contributions to AI and nuclear engineering. Experience integrating machine learning capabilities into established nuclear engineering workflows. Knowledge of optimization methods and their applications in reactor design and fuel cycle analysis. Familiarity with generative models, such as conditional variational autoencoders, for synthetic data generation.
What We Offer
Competitive salary and benefits package, including health, dental, and retirement plans. Flexible work schedules and paid time off to promote a healthy work‑life balance. Professional development opportunities, including mentorship programs and sponsorship for continuing education. An inclusive atmosphere that celebrates new perspectives and supports collaboration between different generations. The chance to be part of a mission‑driven organization making a positive impact on the future of energy. Opportunities for continuous learning and training to grow throughout your career.
Pay: $86,000.00–$136,000.00 per year. Age, disability, veteran status, and other protected class information are reviewed in a non‑discriminatory manner in accordance with the laws and regulations that apply to this position. The company further reserves the right to modify base salary and compensation at any time. All candidates must be U.S. citizens and are required to complete pre‑employment checks, drug screening, and background investigations. The position may require classified/sensitive information clearance. BWXT is committed to Equal Employment Opportunity. All personnel actions such as recruitment, compensation, career development, benefits, training, and social recreational programs are administered without regard to race, color, religion, sex, national origin, citizenship, age, disability, protected veteran status, or other protected status. #J-18808-Ljbffr
Languages
- English
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