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OverviewThis role is responsible for utilizing advanced computer-based simulation tools and engineering principles to analyze, design, and optimize body exterior components and systems. The MDO - Body Exterior CAE Engineer will perform finite element-based studies and multi-disciplinary optimization (MDO) to virtually validate vehicle structure parts, ensuring performance prediction, durability, and safety. This position supports the product development process by providing design guidance, identifying cost and weight savings opportunities, and ensuring designs meet technical specifications and regulatory requirements.QualificationsSkills/Abilities/Competencies:Excellent technical and analytical skills to interpret complex data and provide innovative solutions to technical challenges.Strong ability to work both independently and collaboratively within diverse teams, demonstrating leadership qualities to motivate, encourage, and build consensus.Exceptional self-learning capabilities and a creative mindset, able to quickly assess problems and drive effective responses.Proficient in summarizing and presenting technical work to cross-functional teams and project leads.Ability to balance theoretical knowledge with practical engineering limitations.Highly organized, persistent, and goal-oriented, with the flexibility to rapidly respond to new situations and manage multiple tasks.Awareness of Systems Engineering principles.Fluent in English (oral and written).Highly Preferred Experience:Good understanding of materials properties and advanced mechanics.Demonstrated professional experience in CAE, particularly with a body CAE background, including structural and fatigue analyses.Familiarity with CAE software such as HyperWorks, ANSA, LS-Dyna, Radioss, Abaqus, Nastran, and/or other commercially available FEA programs.Required familiarity with CAE optimization tools like Optistruct, HEEDS, or modeFRONTIER, and morphing tools like ANSA/DEP.Knowledge of automotive product development processes and validation (preferably Ford GPDS).Proficiency in statistical and optimization tools/techniques.Proficiency in programming languages like Python, VB, or MATLAB is a plus.Education/Training:Engineering degree (Mechanical, Mechatronics, Materials Science are highly desirable) or related disciplines with coursework in Finite Element Methods.Master of Science (M.Sc.) or Ph.D. degree preferred.5+ Years of experience/SG8.DFSS Green Belt (or equivalent certification in statistical and optimization tools and techniques) preferred.Ford Motor Company is an Equal Opportunity Employer, as we are committed with a diverse workforce, and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran and basis of disability.ResponsibilitiesDevelop and execute multi-disciplinary optimization simulations, integrating various engineering domains (e.g., structural, safety, NVH, durability) to improve overall product performance for body exterior systems.Analyze and interpret optimization results to propose design modifications that achieve cost, weight, and performance targets for body exterior components.Collaborate closely with design, CAE, and manufacturing teams to incorporate MDO findings into product development and ensure cross-functional alignment.Produce and evaluate solutions to enhance the quality and cost-effectiveness of designs, leveraging specialized engineering knowledge, through Robustness and Sensitive analysisParticipate in global forums and meetings to share technical information regarding new procedures and simulation methodologies.Create, validate, and maintain robust MDO models and workflows to ensure reliable and repeatable simulation outcomes.Perform Topology, Topometry/Topography and other Shape optimizations on component, sub-system and system levelsUse morphing tools to set up parametrization of designsCommunicate optimization insights and recommendations clearly through detailed reports and presentations to technical stakeholders and project leads #J-18808-Ljbffr
