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HRL Laboratories

Research Scientist, Materials Modeling and Processing

Reposted Yesterday
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Hybrid
Malibu, CA
133K-166K Annually
Expert/Leader
Hybrid
Malibu, CA
133K-166K Annually
Expert/Leader
Lead R&D initiatives in materials and digital manufacturing, innovate quality control methods, and utilize machine learning for engineering solutions.
The summary above was generated by AI
General Description:
HRL seeks a creative Scientist or Engineer to join our multidisciplinary team developing new materials and manufacturing processes for automotive, aerospace and defense applications. This role offers the opportunity to make an immediate impact on a high-profile, DARPA funded project shaping the future of metal additive manufacturing. You will also support other programs with materials modeling and simulation and get the chance to propose and lead new programs.   

Essential Duties:
Support and lead cutting-edge R&D initiatives pushing the frontiers of materials, structures and manufacturing approaches for aerospace, defense and automotive applications
Plan and execute analytical and computational analysis and modeling with a focus on continuum methods and digital twin development.
Plan, coordinate, and execute experiments and test campaigns.
Generate ideas for new research programs and write research proposals.
Document inventions and support the patent process.
Communicate with other team members, management, and project sponsors via oral presentations and written reports.
Interact with the broader community by attending and presenting at conferences and publishing in journals.

Required Skills:
Deep understanding of materials science and at least one relevant manufacturing process (metal additive manufacturing, composites manufacturing, laser welding, casting, or stamping).
Experience with Finite Element Analysis FEA (e.g., ABAQUS, COMSOL, MOOSE)
Experience using machine learning libraries such as Scikit-Learn, PyTorch, Keras, or TensorFlow to solve engineering and materials science problems.
Proficiency in programming languages like Python or C++ for data analysis and integration with simulation workflows.
Experience planning, conducting, and analyzing experiments is a plus
Experience in scientific communication through technical presentations and journal publications.
Experience with non-destructing evaluation/inspection techniques such as ultrasonic, eddy-current, X-ray computed tomography and related testing methods is a plus.
Demonstrated expertise in integrated computational materials engineering (ICME) and process – structure – properties relationships is a plus.

Required Education: 
Ph.D. in Materials, Mechanical Engineering, Chemical Engineering, Aerospace Engineering or related discipline. Candidates with additional experience may be considered for more advanced positions.

Physical Requirements:
Must be capable of performing extended analysis at computer workstations
Must be able to work safely in a mechanical testing and additive manufacturing laboratory

Special Requirements:
US citizenship and ability to obtain and maintain US Government security clearance

Keywords: Materials Research and Development, Digital Manufacturing, Additive Manufacturing, Machine Learning, Artificial Intelligence, Materials Informatics


Compensation:
The base salary range for this full-time position is $132,765 - $165,983 + bonus + benefits.
Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range during the hiring process. Please note that the compensation details listed reflect the base salary only, and do not include potential bonus or benefits.

We are proud to be an EEO/AA employer M/F/D/V. We maintain a drug-free workplace and perform pre-employment substance abuse testing.

Top Skills

Abaqus
C++
Comsol
Inventor
Keras
Moose
Python
PyTorch
Scikit-Learn
Solidworks
TensorFlow

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