Job Description:
The key role of this position is to solve challenging engineering problems involving products, systems, and components using advanced simulation techniques and analysis.
此職位的主要職責(zé)是通過仿真技術(shù)和分析解決工程問題。
You will be responsible for ensuring vibration analysis of Cab, light fabrication and Hydraulics meets design requirements, critically evaluate concepts for future products, and work with design engineers to resolve vibration issues.
您將確保與駕駛艙，輕結(jié)構(gòu)，液壓等相關(guān)的振動(dòng)仿真工作滿足設(shè)計(jì)要求，嚴(yán)格驗(yàn)證概念設(shè)計(jì)，并和設(shè)計(jì)工程師一起解決潛在的問題。
What You Will Do
61 Accountable for delivering timely, high-quality simulation and analysis impacting products/processes and providing clear recommendations to stakeholders.
61 負(fù)責(zé)提供及時(shí)、高質(zhì)量的仿真分析，并提供明確的建議。
61 Responsible for defining problem, modeling, solving and performing iterations, interpreting results, providing conclusion.
61 負(fù)責(zé)定義問題，創(chuàng)建仿真模型，運(yùn)行仿真與設(shè)計(jì)迭代，解釋結(jié)果，給出結(jié)論。
61 Partner with design, manufacturing and test to robustly deliver new products and improve validation processes.
61 與設(shè)計(jì)、制造和測(cè)試合作，穩(wěn)健地交付新產(chǎn)品并改進(jìn)驗(yàn)證流程。
61 Keep up to date on new technologies and drive continuous improvement to established techniques.
61 及時(shí)了解新技術(shù)并推動(dòng)現(xiàn)有技術(shù)的持續(xù)改進(jìn)
61 Supporting physical test to verify simulation solutions.
61 支持物理測(cè)試，驗(yàn)證仿真方案
61 Take part in design reviews with the wider design team.
61 與更廣泛的設(shè)計(jì)團(tuán)隊(duì)一起參與設(shè)計(jì)評(píng)審。
61 Responsible for archiving the analysis and simulation model and results
61 負(fù)責(zé)分析仿真模型與結(jié)果的存檔
Degree Requirement
61 Min. MS degree in Mechanical Engineering, Vehicle Engineering, Civil Engineering, Internal combustion engine, Aeronautics / Astronautics, Engineering mechanics or equal, focusing on (all acceptable):
a) Vibration (NVH) test and simulation;
b) Structure fatigue / damage / fracture mechanics test and simulation;
c) Numerical method;
d) Metal / Plastic / Rubber / Composite material experiment and simulation;
e) Reduced order modeling;
f) Integrated Machine Learning