We are seeking to recruit a Postdoctoral researcher with a background in process optimisation for metal Additive Manufacturing (AM). The successful applicant will collaborate within a skilled and motivated team of scientists dedicated to the development of Artificial Intelligence (AI) methods for process optimisation in AM.
The manufacturing industry is facing an increasing pressure to improve efficiency and productivity, whether through maximising throughput, producing customised products, reducing waste (raw materials) and improving environmental sustainability. The increasing efficiency through process improvement is referred to as process optimisation in manufacturing. The adoption of AI and machine learning and AM technologies can significantly improve industrial PO. The goal of the project is to develop AI-based methods for PO in AM. The postdoc will conduct research that contributes to three of the following streams of work 1) define “user needs, goals, procedures” for process optimisation in manufacturing and translate them into solution design specification for an AI-based solution; 2) provide expertise in additive manufacturing to help the research team to implement AI-based algorithms and software for process optimisation in AM; 3) test and evaluate these algorithms on real AM machines and compare them with standard approaches for process optimisation. The position will be under the direction of *Dr. Alessio Benavoli and Dr. Rocco Lupoi.* For informal inquiries please contact alessio.benavoli*@tcd.ie <https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Ftcd.ie%2F&data=05%7C01%7Cuai%40engr.orst.edu%7C2f0b88053dfb48a48f5a08db0b6b8d82%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638116328784496713%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ALe%2FAYB6WBfoc8S1BKXlAVNBx2d37ZAbai3IqvhCwzU%3D&reserved=0>* *Required Qualifications* The successful candidate must have a PhD in Material Engineering, Mechanical Engineering or a related field. The post is applicable to both new and experienced PhD holders, and salary will be commensurate with experience and achievement. *Essential Knowledge & Experience* - Expertise in metal additive manufacturing and experience in characterization and analysis of parts fabricated by laser additive manufacturing - General understanding of the important process parameters in AM and how they characterise the microstructure, property and surface quality of the fabricated part, - Good programming skills, - Established track record of publication in leading journals/conferences, on relevant topics, - Excellent written and oral communication skills, - The ability to work well in a group, - Strong self-motivation and willingness to learn. *Desirable Knowledge & Experience* Experience in one or more of the following areas, is considered is preferable: - Process Optimisation in AM, - AI and Machine Learning, - Industry collaboration. Applicants should submit a cover letter and full Curriculum Vitae to include the names and contact details of 2 referees (including email addresses), no later than the 15th February 2023, via email (subject “Postdoctoral Research Fellow in Process Optimization for Additive Manufacturing”) to: alessio.benav...@tcd.ie Dr. Alessio Benavoli, SCSS, Trinity College Dublin.
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