Research Associate in Machine Learning and Control for Advanced Manufacturing Systems

Contract Type: Fixed-term until 31 July 2022 with a proposed start date of 1 February 2020.
Working Pattern: Full Time
Faculty: Faculty of Engineering
Department: Department of Automatic Control and Systems Engineering
Salary: Grade 7 £31,866 - £40,322 per annum pro-rata. Potential to progress to £41,526 per annum through sustained exceptional contribution.
Closing Date: 5th January 2020

Are you interested in pushing the boundaries of process modelling, control via machine learning with applications in
manufacturing? We have an exciting opportunity in the Department of Automatic Control and Systems Engineering to develop the next generation of machine learning and control methods to advance additive manufacturing (AM) processes (metal 3D printing) for the aerospace sector. You will be working on two affiliated projects - DAM (Developing Design for Additive Manufacturing) and AIRLIFT (Additive IndustRiaLIsation FuTure Technology), with GKN Aerospace the lead industry partner.

In Sheffield research across AIRLIFT and DAM is focused on developing the material properties of AM produced components, designing new in-process metrology including thermal imaging and applying machine learning approaches for the closed loop control of AM processing to achieve 'right first time' manufacturing. You will also be developing computational intelligence models (Machine Learning) for the monitoring and control of industrial
metal additive manufacturing systems. This will include the development of the system’s modelling framework (data-driven modelling), as well as the development of the software interface necessary for the system’s testing and validation.

You will be based in the Department of Automatic Control and Systems Engineering, and you will be expected to also
collaborate closely with industry partners and researchers in the Department of Materials Science and Engineering (additive manufacturing, metallurgy) and the Department of Electrical Engineering (thermal metrology systems).

The post holder will be expected to work effectively as part of project teams, conduct full literature reviews and report their findings through presentations and technical reports. The expectation is that we will develop new theoretical contributions to the field of Computational Intelligence, as well as high impact case studies to demonstrate application in metal AM.

Educated to PhD level (or close to completion), you will have experience in Machine Learning and data-driven modelling, Computational Intelligence methods and algorithms, as well as signal processing for process monitoring, and control, coupled with strong project management and team working skills.

You will be part of a large, growing and well-networked multidiscplinary team at Sheffield. We are well known internationally for our research, and are one of the largest research groups in additive manufacturing in the UK. We lead the MAPP Hub, a £20m Future Manufacturing Hub in Manufacture using Advanced Powder Process funded by the Engineering and Physical Science Research Council (EPSRC). For further information about MAPP please visit www.mapp.ac.uk

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