Doctoral Candidate Position in Production Systems Variation Reduction

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Mathematics and Statistics,Mathematics,Computer Science,Computer Science,Engineering and Technology,Mechanical Engineering,Electrical and Electronic Engineering

Short info about job

Company: Aalto University

Department: Department of Mechanical Engineering

Hours: Full Time

Type / Role: PhD

Phone: +44-1464 3983612

Fax: +44-1555 8247131

E-mail: N\A

Site:

Detail information about job Doctoral Candidate Position in Production Systems Variation Reduction. Terms and conditions vacancy

Aalto University (Espoo, Finland) Department of Mechanical Engineering invites applications for a full-time doctoral candidate position. Please see more information about the Department of Mechanical Engineering http://mecheng.aalto.fi/en/. The position is part of a new Academy of Finland project on Digitalization and the Industrial Internet. 

The goal is to develop digital robust-design variation-reduction solutions using a digital twin: models, wireless data acquisition and data analytics. This will involve engaging both design and production engineering, developing reference models and means to gather data on work-in-progress of a production lines established in the production engineering laboratory. We will develop simulation based root cause analysis to quantify and clarify the main contributors over all production steps across a supply chain. This can involve creating finite-element-analysis models, applying quasi-Monte-Carlo-simulation sampling methods to drive the FEA models to compute uncertainties and sensitivities. This will involve creating demonstrator production cells and creating a wireless data acquisition system. This will involve optimization studies to identify variation reduction strategies.

RequirementsThe call is open for candidates with a Master's degree in mechanical engineering, computer science, applied mathematics or electrical engineering among others. Students graduating in autumn 2017 are also encouraged to apply.

The student involved in this topic is expected to develop expertise in variability data gathering, parametric CAD, FEA, uncertainty quantification, sensitivity analysis and optimization methods. The student will work in the Production Engineering Laboratory, and is expected to also work with Bachelors and Masters students also working either at the laboratory or at company facilities working with engineers on similar quality project. Fluency in Finnish and English is desirable.

The applicant must fulfil the requirements for doctoral students at Aalto University, School of Engineering.  For more details, see: https://into.aalto.fi/display/endoctoraleng/Admission+requirements

EmploymentThe expected duration of doctoral studies is four years (funding is available for 3 years), but a contract is at first made for one year, and the extension is subject to advance of studies and research. The salary is according to the salary system of Aalto University.

How to applyPlease send your application as PDF files by September 30, 2017 through the electronic recruitment system ‘Saima’ https://www.saimanet.com/aaltohome/aew.html?did=5900&lang=fi&job_id=1499&jc=6 and include:

  • CV (1 page)
  • Motivation letter (explain how your background makes you a suitable candidate, why you want to pursue this research and your future professional goals)
  • Certified copy of a master´s degree certificate and official transcript of records, and their translations, if the originals are not in Finnish, Swedish or English.
  • A thesis proposal (2-3 pages – motivation, objectives, approach, related research)

All materials should be in English.

For language requirements, see: https://into.aalto.fi/display/endoctoraleng/Application+instructions#Applicationinstructions-LanguagerequirementsLanguagerequirements

Aalto University reserves the right for justified reasons to leave the position open, to extend the application period and to consider candidates who have not submitted applications during the application period.

For further information about the project, please contact Adjunct Professor Kevin Otto or Laboratory Manager Pekka Kyrenius and for further details about the application process, please contact HR coordinator Merja Seppanen (email: [email protected]).

In Espoo 5.9.2017

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