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  • Job reference: RMS0152868

CAE Analyst - Vehicle - 27305

  • Sector: Automotive
  • Location: Gaydon
  • Job type: Contract
  • Date posted: 18/02/2015
  • Time left:
    d h m s
This vacancy has now expired.
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The Company:
Our Client is a world leading Automotive OEM which is responsible for some of the most iconic 4x4's & Sports Cars produced. Due to the huge demand for current models and substantial investment in future projects there is a requirement for more resources across the business in engineering & manufacturing on a contract basis.

The Role:
Working cross-functionally using the new Virtual Engineering (CAE) Correlation Process on pilot projects that will demonstrative the business benefits, thus gaining senior management momentum behind validation and verification in vehicle development to deliver robust designs. Develop work streams in conjunction with the Product Analysis & Verification Simulation team to develop methods to deliver data for physical testing required to verify simulation methods. Develop expansion of process to physical testing outside of the PAV domain. Develop a process with Virtual Series team to use output from correlation process and pilot projects to drive future data requirements, ensuring data maturity profiles are aligned to the critical delivery path.

Essential Skills / Qualifications:
One or more of LS-Dyna/Abaqus/Star CCM+/Power FLOW Able to communicate complex technical concepts Good communication and relationship building skills Be results driven and meet commitments. You should strive to seek out improvements to business processes to support customer service & business financial objectives. A positive attitude and flexibility to adapt to changing work requirements and priorities.
A CAE background - One or more of LS-Dyna/Abaqus/Star CCM+/Power FLOW Experience of physical testing related to CAE methodologies Understanding of RMDV and PCDS and Virtual Series Delivery of Engineering and or analytical projects preferably within the automotive industry. Experience of solving complex technical issues using a structured approach with the ability to identify areas for improvement, preferably with experience of six sigma methodologies.
Engineering Degree
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