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Combining machine learning and closed-loop control theory


About This PhD Project

Project Description

The successful student will work with Professor Andrew Parnell and Professor Subhra Dey’s research groups as part of the new SFI I-Form centre on analytics for advanced manufacturing. The student will form part of a research cluster that includes University College Dublin, Trinity College Dublin, Dublin City University, National University of Ireland Galway, and Institute of Technology Sligo. The candidate will work on advanced statistical and machine learning approaches to manufacturing data as part of Platform 3: Advanced Analytics and Engineer Feedback. This will involve taking large data sets of streamed sensor data from manufacturing equipment and developing models that predict machine health and the interaction between the machine operator and the machine tool. Application areas include medical device manufacturing and 3D printing. Many of these application areas have industry partners and the chosen candidate may follow either academic development or industry participation as they see fit.

All applicants must have
• Relevant 2:1 degree (or higher) in Mathematics, Engineering, Physics, Computer Science, Statistics, Machine Learning, Data Science, or similar qualification
• Ability to code in one or more of Matlab, C, R or Python
• Strong linear algebra and calculus skills
• Excellent written and verbal communication and presentation skills in English

The studentships are for 48 months and include a tax free stipend of €18,500 p.a. and the payment of academic fees up to a maximum of €5,500 per annum, as well as a computer and travel allowance.

Application Procedure: send a curriculum vitae and a cover letter to with PHD X in the subject line indicating the desired PhD project. Candidates are allowed to express interest in multiple PhD proposals

Closing Date: 4th January 2019.

Interview: Date to be advised. Appointments from January/February 2019.

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