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: It is advantageous to have experience in one or more of the following areas: -Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization) -Additive
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. Gaussian Process Regression) model to describe the relationship between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set
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exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised
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and BAT.jl projects. The position also offers opportunities to contribute to research in Bayesian inference and its application to physics in general. The DEMOS project aims to develop state-of-the-art
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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. Image-based acquisition of the current state of arbitrary object geometries has
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objects. Different acquisition devices are used depending on the object properties and quality requirements. A new robot-based multi-sensor platform will combine the existing technologies to enable a
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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industrial objects. Different acquisition devices are used depending on the object properties and quality requirements. We research modern machine-learning methods for the analysis of an object's optical
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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. Calibration of 3D scanning technologies is the critical first step for the accurate
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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. Through regular scanning missions and assignments, 3D scans of diverse objects