Research Associate

4 weeks ago


Lancaster, United Kingdom Lancaster University Full time

We wish to appoint a talented researcher to undertake advanced research in the field of process monitoring and optimisation of metal additive manufacturing, part of the collaborative project “Intelligent Advanced Additive Manufacturing - Enabling Dynamic Process Efficiency (iAM-3DPO)” with multiple industrial partners funded under Innovate UK.

The iAM-3DPO project aims to address this using a multidisciplinary approach by implementing an advanced laser system, coupling real-time data acquisition from optimised optical and thermal monitoring systems, with a data-driven approach that uses modularized AM data, cloud-based computing, machine learning, and adaptive machine process parameter control to achieve zero-distortion, zero-defects builds. The advanced AM process technology and adaptable optimisation approach will result in cost reduction, higher material utilization, improved quality assurance, product customization and reduced design cycle times in the AM process chain.

Lancaster University as one partner of the entire project, will focus on process optimisation and the integration of all the developed modules in different WPs and perform the industrial trials in each of the use cases targeted. Your required tasks include:
i) Develop AI-based process monitoring module using various sensors for defect detection

ii) Build effective process optimisation algorithms to optimise process parameters

iii) Integration of monitoring data, optimisation techniques and control module in LPBF AM platform.

iv) Testing and trial of iAM-3DPO in manufacturing of metal product samples.

v) Performance verification and final customisation of iAM-3DPO system.

vi) Writing reports for related tasks and publications

You must hold a MSc or PhD in a relevant discipline, and related academic or industrial experience at post-doctoral or commensurate level is highly desirable; excellent team-working and communication skills are also required.

The position is available to engineers / data scientists with experience of implementing data analytics in a manufacturing environment.

You will join us on a full-time, indefinite contract however, the role remains contingent on external funding which, at this time is until 30/09/2024

Lancaster University is campus-based, and located close to the Lake district in the north-west of England; the University also enjoys excellent public transport and national rail links. Lancaster is just one hour from international airports at Manchester, Liverpool and Leeds. The town and the region are home to a variety of excellent schools and enjoy excellent public transport and national rail links. A wide selection of facilities is available on campus including a large variety of social facilities, eateries, a new sports centre, and a highly regarded pre-school centre.



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