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Field
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Challenge: Distinguish noise and signal in data streams Change: Refined asymptotic analysis of stochastic processes Impact: Faster detection of anomalies and reliable uncertainty quantification Job
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interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and
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interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and
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develop your software engineering skills to redefine manufacturing? This exciting PhD project is for you if you want to develop innovative techniques to ensure industrial robots are reliable, safe, and
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of data in situ, as close as possible to the point of capture, is also a very important objective for reliable and self-calibrated water quality measurements. Scientific and technological barriers: Sensor
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transition, with an increasing need to deploy large-scale offshore wind turbines in harsh operational environments. As these systems grow in complexity and power rating, ensuring the reliability of generator
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fall short—paving the way for smarter perception, enhanced safety, and reliable all-weather situational awareness in future vehicles. Terahertz frequencies (0.1–10 THz) offer unique advantages, including
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current quality control practices are often fragmented and reactive. To move towards a more reliable and circular manufacturing approach, we need intelligent quality control systems that can adapt in real
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potential pathway to employment with Codan after completion of the PhD. About Codan Codan Limited is a global group of electronics and engineering businesses that develop rugged and reliable hardware
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solutions in digital agriculture. Working closely with the Data Center Director and interdisciplinary teams, the Specialist will help manage infrastructure, develop analytics workflows, ensure data quality