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the predictions of opaque models that are widely deployed in high-stakes decision making scenarios. Of particular interest to this project are example-based explanation methods that use individual data points
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Management and Analysis: Compile and analyze experimental data, comparing results with theoretical predictions to assess data quality. Technical Documentation: Prepare detailed reports and contribute
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, comparing results with theoretical predictions to assess data quality. Technical Documentation: Prepare detailed reports and contribute to scientific publications. Operates, maintains, and troubleshoots
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measurement campaign using high-speed imaging and in-line force measurements on actual textile manufacturing machinery in collaboration with leading industrial partners. The goal is to develop a predictive
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are essential to the biological function of all organisms. For example, haemoglobin must change conformation to bind oxygen and fulfil its biological function. While machine learning approaches that predict
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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of predictive models for energy demand and production. These models will leverage techniques such as time series analysis and machine learning and will be integrated into a digital twin platform. The aim is to
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the impact of molecular rearrengements on the performance, shelf lifetime and stability of electronics. Our goal is to define a physical framework capable to predict relevant timescales.The successful
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. The sub-project of the Phytophotonics department focuses on analysing hyperspectral imaging data for predicting infestations in field crops. The focal topics of the sub-project include: Realisation of a
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. The areas of responsibility include: Develop computer vision and AI models for detecting wind turbine blade damage and predicting its progression, with experimental validation carried out at DTU test