High Value Manufacturing Engineer in Artificial Intelligence (KTP Associate)

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This is an exciting opportunity for an ambitious graduate with the ability and confidence to manage a Knowledge Transfer Partnership (KTP) project with Oxford Engineering Ltd (OE).   ​​​

​The University of Manchester and OE are looking to recruit a High Value Manufacturing Engineer in Artificial Intelligence to undertake this 30 month project which has an overall aim of optimising machining strategy through data driven manufacturing planning processes.

The position will provide the successful candidate with a unique opportunity to work on the interface between university and business at the cutting edge applications of artificial intelligence. Different from the conventional rule-based methods, this will lead to completely new and flexible methods as big-data driven process planning for machining. The candidate will have the rare opportunity to develop links to the manufacturing industry and demonstrate the state-of-the-art interdisciplinary research in CAD/CAM and machine learning at the University of Manchester.

Candidates will require a PhD (or equivalent) degree in Mechanical Engineering (or a PhD degree in other strongly relevant engineering programmes such as Industrial Engineering / Electrical Engineering) and strong research record in computational design, advanced manufacturing and robotics. Excellent skills in C++ programming and mathematics formulation are required. Experiences in CAD/CAM software development are expected. Candidate will also need to conduct programming in Python.

This post is funded through a Knowledge Transfer Partnership (KTP) award, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and industry.

Based at OE in Abingdon, Oxfordshire, the successful candidate will work directly with supervisors from both the University and OE and will use the facilities and resources of both organisations

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status.  All appointments are made on merit.

Our University is positive about flexible working – you can find out more here

Blended working arrangements may be considered

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Enquiries about the vacancy, shortlisting and interviews:

Name: Prof. Charlie C.L. Wang

Email: changling.wang@manchester.ac.uk

General enquiries:

Email: hrservices@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.