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  • Job reference: RMS0148557

CAE Analyst - 27289

  • Sector: Automotive
  • Location: Gaydon
  • Job type: Contract
  • Date posted: 13/07/2015
  • Time left:
    d h m s
    (06/08/15)
This vacancy has now expired.
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:
This vacancy is for the role of CAE engineer to carry out vehicle level NVH studies in support of pre programmes and programmes commencing Virtual Series. Vehicle NVH CAE engineer works in a complex and demanding CAE environment requiring both CAE and NVH in-depth understanding and experience. Sub-system CAE models are built into whole vehicle models, correlated, analysed, and then used to identify potential whole vehicle NVH issues. The models are then utilised to understand route causes and to identify and verify potential NVH solutions at component and systems level.

Essential Skills / Qualifications:
• Full Vehicle modelling within the Nastran environment including test/CAE hybrid approaches.
• Programming experience (eg VBA, C++, FORTRAN, TCL) would be beneficial.
• Experience of using commercial simulation/test products (e.g Hyperworks, Virtual.Lab, Test.Lab, modeFrontier, Simpack)
• Experience of data collection and analysis on vehicles (track / dyno) and modal test
• Experience of VNVH vehicle assessment, VET Dri
• Experience of solving complex technical issues using a structured approach with the ability to identify areas for improvement.
• Candidates should be educated to Degree level in Mechanical, Automotive or another related engineering discipline and have 5 years minimum directly related experience

Desirable Skills / Qualifications:
• Non-linear, vibro-acoustic modelling using such as NASTRAN, LMS-VIRTUAL LAB or other codes
• Experience in hybrid modelling in both LMS Virtual.Lab and Test.Lab environment.
• Green-belt trained
• Knowledge of GPDS processes.
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