채용
An Interior Systems CAE Engineer is a specialized professional responsible for applying advanced Computer-Aided Engineering (CAE) methods to analyze and optimize automotive interior components. This role involves developing and utilizing Finite Element Analysis (FEA) models to understand complex physical phenomena and predict the performance of parts like cockpit and trim, seat structure, seat plastics, and overhead systems. The engineer's primary objective is to leverage these simulation tools to provide fundamental insights, advance product designs, perform optimizations, and offer design recommendations. This ensures that interior system designs are robust, manufacturable, cost-effective, and meet all necessary internal quality and customer requirements through close collaboration with cross-functional teams. This position offers a unique opportunity to directly influence product development from concept to production, working within a collaborative, cross-functional environment.
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Engineering degree (Mechanical, Biomechanics, Mechatronics, Materials) or related disciplines with coursework in Finite Element Methods. MSc / Ph. D. degree preferred.
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Proficiency with industry-standard finite element software (e.g., Abaqus, LS-Dyna, Nastran, Ansys, Hyper Works, etc.).
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Ability to analyze and interpret simulation results to provide actionable design recommendations.
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Excellent problem-solving skills and a strong analytical mindset.
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Effective communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
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Familiarity with automotive interior systems (hard trim, seat plastics, overhead systems) is highly desirable.
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Independent, self-motivated, goal oriented, highly organized and persistent.
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Able to work both independently and effectively with others.
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Passion to overcome challenges and keep learning.
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Be proactive for finding solutions to given issues.
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Fluent in English (oral and written).
Highly Preferred Experience
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Engineering Knowledge of Mechanical and Structural concepts: Linear / Nonlinear, Dynamics, as well as Implicit and Explicit knowhow.
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Experience with test correlation and validation of CAE models against physical test data.
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Proven expertise in setting up, running, and post-processing FEA models using industry-standard software packages (e.g., Abaqus, LS-Dyna, Nastran, Ansys, Moldfow, Moldex3D, Opti Struct, Radioss).
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Experience with Team Center/Catia Environment and/or 3DX
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Strong understanding of material properties and their behavior under various loading conditions (elasto-plasticity, rheology, stress-strain etc..).
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Familiarity with automotive industry standards and regulations (e.g., FMVSS, ECE regulations).
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Knowledge of optimization algorithms and design of experiments (DoE) principles.
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Knowledge of automotive product development processes and validation (GPDS).
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Grounded in engineering principals and applications of static, dynamic and low speed impacts analyses for engineering design and performance requirements.
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Knowledge of plastics injection processes for automotive parts.
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Demonstrated ability to devise, create, or adapt novel analysis methods.
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Evidence of technical excellence as indicated by technical presentations and reports.
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Develop, execute, and validate detailed Finite Element Analysis (FEA) models for a wide range of interior components, including hard trim and overhead systems (e.g., headliners, sun visors, overhead consoles).
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Utilize Computer-Aided Engineering (CAE) methods as primary tools to gain fundamental understanding of complex physical behaviors within interior systems.
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Provide data-driven insights and design recommendations to cross-functional teams, actively driving design improvements and optimizations.
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Collaborate closely with design, engineering, and manufacturing teams to ensure designs meet all necessary internal quality standards and customer requirements.
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Identify opportunities for cost-effective design solutions while maintaining or enhancing product performance and quality.
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Interpret simulation results, generate comprehensive reports, and present findings clearly and concisely to various stakeholders.
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Contribute to the continuous improvement of CAE methodologies, tools, and processes.
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Conduct root cause analysis for design failures or performance deficiencies identified through testing or field issues, providing data-driven recommendations for corrective actions.
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Clearly communicate complex technical concepts and simulation results to both technical and non-technical stakeholders.
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Participate in design reviews, peer reviews, and technical discussions, contributing expertise to drive consensus and informed decision-making.
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Contribute to the continuous improvement of CAE processes, best practices, and simulation toolchains to enhance efficiency and accuracy.
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Ford 소개

Ford
PublicThe Ford Motor Company is an American multinational automobile manufacturer headquartered in Dearborn, Michigan, United States. It was founded by Henry Ford and incorporated on June 16, 1903.
10,001+
직원 수
Dearborn
본사 위치
$48B
기업 가치
리뷰
3.3
10개 리뷰
워라밸
3.8
보상
3.5
문화
2.8
커리어
2.2
경영진
2.5
45%
친구에게 추천
장점
Good benefits
Good work-life balance
Strong management support/respect
단점
Poor/terrible management
Limited career growth opportunities
High turnover
연봉 정보
21개 데이터
Mid/L4
Senior/L5
Mid/L4 · ADAS Data Analytics Engineer
1개 리포트
$132,847
총 연봉
기본급
$102,190
주식
-
보너스
-
$132,847
$132,847
면접 경험
3개 면접
난이도
3.0
/ 5
소요 기간
14-28주
경험
긍정 0%
보통 67%
부정 33%
면접 과정
1
Application Review
2
Phone Screening
3
Technical Interview
4
Team Interview
5
Offer
자주 나오는 질문
Technical Knowledge
Behavioral/STAR
Past Experience
Coding/Algorithm
뉴스 & 버즈
Trump Administration Wants Ford, GM To Produce Weapons And Munitions Amid Wars In Iran, Ukraine: Report - Yahoo Finance
Yahoo Finance
News
·
2d ago
Ford recalling nearly 1.4 million F-150 pickup trucks over unexpected downshift issue - WKBN.com
WKBN.com
News
·
3d ago
USS Gerald Ford returns to Mideast as 3rd American aircraft carrier heads to region - The Times of Israel
The Times of Israel
News
·
3d ago
Ontario Premier Doug Ford criticised for $21m private jet purchase - BBC
BBC
News
·
3d ago