Nuclear Engineering Data Scientist

BWX Technologies, Inc.; Virginia (MN); Sur place; USD 150 000 - 210 000; Plein temps

Résumé du poste

BWX Technologies, Inc. (BWXT) is seeking a Nuclear Engineering Data Scientist to drive AI-enabled nuclear engineering solutions. The role focuses on integrating ML into engineering workflows for safety and performance, leveraging deep learning and physics-based models in a leadership capacity.

You will work on advanced modeling, uncertainty quantification, and data-driven optimization within a high-security, nuclear-focused environment. This on-site role is based in Lynchburg, VA.

Qualifications

• Bachelor's degree in Nuclear Engineering, Computer Science, or related field with ML focus.
• 10+ years of relevant experience in ML for engineering or nuclear domains.
• Proven expertise in TensorFlow and PyTorch.
• Proficient in Python, C++, and MATLAB.
• Experience with MCNP, Serpent, OpenMC, and CTF.
• Strong track record in hybrid modeling and uncertainty quantification.
• Excellent communication and publication record; U.S. citizenship.

Responsabilités

• Develop and deploy ML models for nuclear engineering problems.
• Design hybrid physics-data modeling frameworks for reactor physics and safety.
• Implement uncertainty quantification to ensure robust predictions.
• Optimize nuclear engineering processes with advanced AI methods.
• Collaborate with cross-functional teams to integrate ML tools.
• Lead data augmentation and domain adaptation in data-scarce contexts.

Connaissances

Machine learning expertise

Hybrid modeling

Uncertainty quantification

Transfer learning

Data augmentation

Publication record

Strong communication

Formation

Bachelor's degree in Nuclear Engineering, Computer Science, or related field

Outils

TensorFlow

PyTorch

Python

C++

MATLAB

MCNP

Serpent

OpenMC

CTF

Description du poste

At BWX Technologies, Inc. (NYSE: BWXT), we are People Strong, Innovation Driven. A U.S.-based company, BWXT is a Fortune 1000 and Defense News Top 100 manufacturing and engineering innovator that provides safe and effective nuclear solutions for global security, clean energy, environmental restoration, nuclear medicine and space exploration. With more than 7,800 employees, BWXT has 14 major operating sites in the U.S., Canada and the U.K. We are the sole manufacturer of naval nuclear reactors for U.S. submarines and aircraft carriers. Our company supplies precision manufactured components, services and fuel for the commercial nuclear power industry across four continents. Our joint ventures provide environmental restoration and operations management at a dozen U.S. Department of Energy and NASA facilities. BWXT's technology is driving advances in medical radioisotope production in North America and microreactors for various defense and space applications. For more information, visit www.bwxt.com . Follow us on LinkedIn (https://www.linkedin.com/company/bwx-technologies/mycompany/?viewAsMember=true) , X (https://twitter.com/BWXT) , Facebook (https://www.facebook.com/BWXTech) and Instagram (https://www.instagram.com/bwxtechnologies/) .

Welcome to BWXT

We believe in empowering our employees and cultivating a dynamic workplace that fosters growth and collaboration. Whether you're an experienced professional or just starting your career, you'll find opportunities to challenge yourself, learn from seasoned experts, and contribute to nuclear innovation. We required a diverse range of skills to support our work in the markets that drive our business and welcome candidates from all backgrounds and life stages who are passionate about making a difference.

Position Overview

As our Nuclear Engineering Data Scientist, you will leverage advanced machine learning techniques, hybrid modeling approaches, and uncertainty quantification to tackle complex problems in nuclear engineering and related domains. This role is perfect for someone with a strong research background, experience in integrating machine learning models into engineering workflows, and a passion for applying cutting-edge AI technologies to real-world challenges in the nuclear industry.

Location

This position is based on-site in Lynchburg, VA at the Advanced Technologies Office.

Your Day to Day as a Nuclear Engineering Data Scientist

• Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), 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 is required.
• Must have proven expertise in deep learning frameworks such as TensorFlow and PyTorch.
• Must be proficient in programming languages and tools, including Python, C++, and MATLAB.
• Must have experience with nuclear codes such as MCNP, Serpent, OpenMC, and CTF.
• Must have demonstrated ability to develop and validate hybrid modeling techniques in nuclear engineering contexts.
• Must be familiar with uncertainty quantification methods and transfer learning techniques.
• Must have strong publication record in reputable journals and conferences, showcasing contributions to AI and nuclear engineering.
• Must have excellent communication skills and ability to present complex technical concepts to diverse audiences.
• Must be a U.S. citizen.
• Must be able to obtain and maintain a U.S. Department of Energy (DOE) or Department of Defense (DOD) security clearance as required.