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, and implementation of these advanced materials. Information and application To apply, please submit your application before September 30, 2025, via the "Apply now" button. Your application must include
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technology. To help ground your research statement, we recommend you study the Futures of Language project description(link is external) and identify which strands you are most passionate about. The first
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of efficient control strategies and promoting continuous improvement, to speed up production and ensure product quality. This research could revolutionize Philips’ production by integrating advanced Artificial
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
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of efficient control strategies and promoting continuous improvement, to speed up production and ensure product quality. This research could revolutionize Philips’ production by integrating advanced Artificial
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well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest
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uncertainty". The goal of this project is to advance our understanding of how humans are able to act in complex and uncertain circumstances, and how such knowledge can be applied to smooth our interaction with
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Future-Proof Smart Logistics. It aims to contribute to the realisation of the PI concept by developing advanced machine learning-based decentralised decision-making algorithms. These algorithms will enable
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external link , as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our
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materials performance. Developing the understanding of the piezoelectric film structures and their functional properties using characterization techniques such as AFM, XRD, SEM and DBLI and detailed analysis