Role Description & Responsibilities:

The North America (NAM) Modelling & Simulation (MODSIM) team creates AI-enabled simulation-driven design solutions across the CATIA, SIMULIA and SOLIDWORKS brands of Dassault Systèmes.

Our team delivers technical solutions, sales and marketing assets to targeted markets for all industries spanning from high-tech and life sciences to aerospace and transportation.

Analyze customer requirements and the industry and market landscape to assist the marketing and/or sales team in identifying new business opportunities with a special focus on AI-powered MODSIM

Create content to support key go-to-market initiatives for next generation of MODSIM and AI technologies on the 3DEXPERIENCE Platform based on industry needs

Interact with customers interested in using Dassault Systèmes products with a special focus on next generation of AI integrated Modeling and Simulation tools

Support and collaborate with R&D teams to bridge the gap between AI-Powered MODSIM technology and the needs of the industry

Qualifications:

• Actively enrolled in Master’s or PhD program in Mechanical, Aerospace or related engineering field
• Minimum cumulative GPA 3.3
• Coursework or equivalent background of one or more physics domains such as electromagnetics, fluids, motion, plastic injection molding and/or structures. Computational modeling coursework (CFD, FEA, etc.) preferred.
• Coursework or equivalent experience using 3D design tools such as 3DEXPERIENCE, CATIA or SOLIDWORKS with a focus on creating parametric 3D models desired
• Working knowledge in Deep Learning Architectures for CAE/FEA surrogate modelling using ML frameworks such as TensorFlow or PyTorch
• Ability and willingness to self-teach new and advanced software functions; coaching and instruction will be provided
• Ability to handle multiple projects/tasks simultaneously
• Demonstrate problem solving skills illustrating the ability to create engineering solutions to engineering challenges
• Excellent verbal communication and presentation skills