High Value Manufacturing Engineer in Artificial Intelligence - KTP Associate

£33,309 - £40,927

Abingdon-on-Thames, Oxfordshire - 30 months

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Job description

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.

Project description

To develop, embed and exploit advanced smart manufacturing and data-driven machine learning techniques that can be implemented and adopted to deliver automated manufacturing process planning.

About the business

Oxford Engineering Limited of Abingdon, Oxfordshire specialises in lean manufacturing, supply chain management and precision engineering to provide total manufacturing solutions. Our mission is to be “an engineering company worthy of high regard” (as featured in Timothy Forster’s, ‘101 Great Mission Statements’ — How the world’s leading companies run their businesses. A collection of mission statements from leading organisations from all over the world, selected by experts in the field. Organisations such as Coca-Cola, Mc Donalds, Toyota, Ford, British Airways, Johnson&Johnson, American Express, Apple Computer, IBM, Microsoft, British Telecom, Bayer, Glaxo, Federal Express, Tesco, W H Smith…). We have the ability and the experience to provide cost competitive, lean, low risk manufacturing solutions to a wide variety of demanding industry needs. Since its formation in 1968, Oxford Engineering Limited has built an extensive expertise in a number of selected focused industry sectors; namely Medical, Energy (Oil and Gas & Power Generation), Semi conductor and Aerospace. The key to the company’s success is customer focus, with 90% of business resulting in repeat work from clients, many of whom have trusted the Company as a single source for over 25 years.

Engineering

Mechanical Engineering

PhD (or equivalent) degree in Mechanical Engineering (or a PhD degree in other strongly relevant engineering programmes such as Industrial Engineering / Electrical Engineering)

24 November 2021

8 December 2021

SAE-017908


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.