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Field
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of £25,726 plus a research training support grant of £20,000 and 100% fees paid. Overview This PhD project aims to develop a computationally efficient framework for the real-time prediction of river water
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addresses two intertwined goals: Improving Human Training: Developing adaptive haptic training strategies that help operators refine their skills through real-time skill estimation, multimodal feedback, and
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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Description Challenge: Uncovering the interdependency between telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency
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about the department at www.es.aau.dk . Description of the position The position focuses on developing next-generation learning-based decision-making and control for autonomous robots operating safely in
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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
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edge computing. Motivated candidates with strong mathematical and/or algorithm development backgrounds are especially sought. KIOS Research and Innovation Center of Excellence (KIOS CoE) The KIOS
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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
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or damage. Along these lines, this project develops SHM methods for deep tunnels, with the HADES Underground Research Laboratory (URL) serving as the primary case study. The monitoring strategy combines in
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory