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HL
HRL Laboratories
Computational Scientist, Metal Additive Manufacturing
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What they do
An Additive Manufacturing Engineer develops and executes manufacturing process plans for additive manufacturing, which use a range of laser-based or advanced printing techniques to build up models layer by layer. Improves processes and plans, designs and executes tooling requirements. Develops operator training courses.
$113,328 / year median in California
+14% projected growth
Job Description
HRL Laboratories pioneers the next frontiers of physical and information science. Delivering transformative technologies in automotive, aerospace and defense, HRL advances the critical missions of its customers to help them remove limitations and create competitive advantage. HRL then transitions the work back to customers - ready for real-world application. For more than 70 years, HRL's rich portfolio of scientific discoveries and engineering innovations continues to build on each other — often in unexpected, profound and far-reaching ways. As a private company owned jointly by Boeing and GM, HRL prioritizes purpose over profit, significantly advancing the state of the art. HRL Laboratories advances critical structural and functional materials and semiconductor devices that enable precision navigation, quantum technologies and extreme-environment performance. With expertise from design through deployment, we deliver scalable, high-performance solutions that transform our customers' missions. Our work leverages digital manufacturing and scalable microfabrication techniques to meet tomorrow's toughest challenges.
Position Summary:
In this role, you will have the opportunity to make an immediate impact on a high-profile, America Makes funded project shaping the future of metal additive manufacturing. The ideal candidate will have an interest in growing into a Principal Investigator (PI) that will conceive, propose and lead new research initiatives.Essential Duties:
- Support advanced R D programs [TS1.1]in metal additive manufacturing, working closely with interdisciplinary teams to drive scientific and technological breakthroughs
- Plan and execute analytical and computational analysis and modeling with a focus on continuum methods and digital twin development
- Communicate complex modeling results clearly through presentations, technical reports, and collaborative discussions with team members, management and project sponsors
- Translate fundamental materials and process understanding into practical, scalable solutions for real-world additive manufacturing applications
- Plan and manage key project components—including timelines, deliverables, and resources—to ensure successful execution and meaningful impact
- Collaborate with experimental teams to validate models, compare simulation outputs with measurement data, and refine predictive capabilities.
- Interact with the broader community by presenting at conferences and publishing in journals
Required Qualifications:
- PhD or Postdoctoral experience in Materials Science, Mechanical Engineering, or a related field
- Strong foundation in computational modeling and familiarity with current and emerging AI/ ML methods relevant to materials and process optimization
- Experience with Finite Element Analysis FEA (e.g., ABAQUS, COMSOL, MOOSE)
- Experience with mesoscale microstructure modeling techniques such as phase field, cellular automata, and kinetic Monte Carlo methods
- Proficiency in programming languages like Python or C++ for data analysis and integration with simulation workflows
- Experience using machine learning libraries such as Scikit-Learn, PyTorch, Keras, or TensorFlow to solve engineering and materials science problems
- Experience with Scientific Machine Learning (SciML) for surrogate model development
- Experience in scientific communication through technical presentations and journal publications
Preferred Qualifications:
- Experience planning, conducting, and analyzing experiments
- Experience with Laser Powder Bed Fusion metal additive manufacturing
Physical Requirements:
- Ability to perform extended computational modeling and analysis at a workstation
Special Requirements:
- U.