R&D Textile Composite Modeling Engineer

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Cadence is a pivotal leader in electronic design, building upon more than 30 years of computational software expertise. The company applies its underlying Intelligent System Design strategy to deliver software, hardware and IP that turn design concepts into reality. Cadence customers are the world’s most innovative companies, delivering extraordinary electronic products from chips to boards to systems for the most dynamic market applications including consumer, hyperscale computing, 5G communications, automotive, aerospace, industrial and health.

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Location:

Mont Saint Guibert, Belgium

Reports to:

Sr Software Engineering Manager

As an R&D Textile Composite Modeling Engineer, you will be at the forefront of developing next-generation multiscale simulation technologies for textile composite materials within Cadence’s DIGIMAT product suite. This role sits within a collaborative R&D team whose work directly enables engineers across the automotive, aerospace, defense, energy, and industrial sectors to predict material performance with greater accuracy and efficiency. You will combine deep expertise in composite materials science, virtual manufacturing, and software development to translate research into robust, production-ready simulation capabilities used by some of the world’s most innovative manufacturers.

• Design and implement multiscale material models for textile composites, including woven, braided, NCF, and 3D woven architectures within the DIGIMAT simulation platform.
• Develop virtual manufacturing workflows that capture the influence of manufacturing processes (draping, infusion, RTM, compression molding, and curing) on composite material performance.
• Build and validate homogenization methods and continuum mechanics models covering damage and failure behavior for a range of composite material systems.
• Create and maintain automated workflows for textile composite model generation, characterisation, and correlation against experimental data.
• Contribute to and lead R&D projects spanning the full lifecycle from concept and algorithm development through to industrial deployment and customer validation.
• Collaborate with materials scientists, manufacturing engineers, and software developers to integrate new simulation capabilities into production-quality software releases.
• Engage with industrial partners and customers to understand application requirements, present technical findings, and gather validation feedback.
• Apply software engineering best practices - including version control (Git/SVN), containerisation (Docker), testing, and CI/CD pipelines - to maintain code quality and release reliability.
• Identify and evaluate emerging technologies, including AI/ML-assisted simulation acceleration, to continuously advance the state of the art within the DIGIMAT roadmap.

• PhD in Engineering, Materials Science, Mechanical Engineering, Applied Mathematics, or a closely related discipline - or equivalent demonstrated research and industry experience.
• 5-8 years of post-doctoral or industrial R&D experience in composite materials modeling, with direct expertise in textile composites and multiscale simulation methods.
• Advanced knowledge of composite material modeling and simulation, including homogenization, continuum mechanics, and damage and failure modeling.
• Strong understanding of textile composite architectures (woven, braided, NCF, 3D woven) and their relationship to manufacturing processes and structural performance.
• Proficiency in at least one of C++, C#, or Python, with experience developing and validating simulation software in a research or commercial environment.
• Familiarity with finite element platforms such as Abaqus, Marc, LS-DYNA, Nastran, or similar tools.
• Experience working with software development practices including Git or SVN, Docker, automated testing, and CI/CD workflows.
• Strong scientific…