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the theory of optimization algorithms and high-dimensional statistics to address some of the most fundamental questions in ML such as the behavior of neural networks. The environment of this project is highly
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strengthen your application: Experience with computational ship hydrodynamics Experience with STAR-CCM+ and Abaqus Knowledge of Control Algorithms (e.g. PID controller) Knowledge of Reduced Ordered Models What
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write your thesis in the context of the research project ‘Tracing the Realities of Algorithmic Warfare: From Innovation to Deployment and its Impact on Civilian Harm,’ funded by the Research Foundation
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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networks, making use of intelligent AI-driven control planes. The work will involve: i) (i) development of network probing algorithms for OSNR/GSNR measurement automation; (ii) development of adaptive ML and
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the following research areas providing a template for relevant directions: Research Topics: -Distributed task planning and navigation for collaborative manipulation -Motion planning for non-circular unsymmetric
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from motion blur, defocus, and imaging artefacts, which hinder accurate diagnosis. This project aims to restore image clarity by designing intelligent algorithms that recover fine anatomical details
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toward safe AI control systems. The candidate will be part of the Distributed, Embedded and Distributed Systems research group: https://www.cs.aau.dk/research/distributed-embedded-intelligent-systems
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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research lines. Research line 1: "Digital twinning for 3D network optimization" focuses on developing distributed digital twin architectures and mechanisms for distributed network optimization in networks