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Field
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). The candidate should have hands-on experience developing state-of-the-art machine learning models, particularly deep neural networks (experience with graph neural networks is highly valued). Their background
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to WAN and inter-domain networking, Excellent command of foundational and applied AI technology, from neural networks, distributed reinforcement learning to agentic AI and recent developments in
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addresses this challenge in two ways: We investigate the fundamental neural mechanisms that control movement. We explore engineering-based solutions to restore function when these pathways are disrupted. As a
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-tracking and behavioural measurements. As a PhD Candidate, you will be part of an international network of 13 research labs located throughout Europe working on the EU-funded HUM.AI.N-ACCENT project
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organisms age or how our DNA is repaired, to how epigenetics regulates cellular identity or neural memory. Activities and responsibilities The research group of Katja Luck offers the following PhD project
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, C++, ROS, ML/AI frameworks such as PyTorch/TensorFlow). Background in at least one of: intelligent robotics, neural networks, cyber-physical systems, or explainable AI. Excellent English communication
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of electrical topologies (AC, DC, three-phase) and will integrate both standard and atypical wear cases. On this basis, high-performance artificial intelligence models will be developed. By combining neural
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this, we focus on self-supervised denoising, where models learn to restore images using only the noisy data itself — without requiring clean references. Existing approaches often rely on convolutional neural
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-fidelity modelling, physics-informed machine learning, deep learning, transfer learning, physics-informed neural networks, neural operators, reinforcement learning, adaptive sampling. Duties of the position
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part of an international network of 13 research labs located throughout Europe who work on the EU funded HUM.AI.N-ACCENT project. The full consortium count with a total of 24 academic and non-academic