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Is the Job related to staff position within a Research Infrastructure? No Offer Description Computational geometry is the area within algorithms research dealing with the design and analysis
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that are both fast and adaptive? This thesis aims to develop a robust hybrid learning framework that lies at the nexus of online and offline learning. The developed algorithms should be able to benefit from
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May 2026 Apply now Are algorithms neutral tools, or do they actively shape the world they model? In this PhD, you will bridge the gap between building and critically studying Human-Centred AI systems
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a focus. Traditionally, this is done through iterative algorithms (‘trial and error’). In this project, we aim to develop a radically different approach where the correct shape is computed using a 3-D
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our biofeedback algorithms and, after small N assessments, contribute towards setting up a large-scale trial to assess the efficacy of the newly developed methods. For this you will interact extensively
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for their governing mechanisms? How can we make these model computationally efficient and capable of scaling to large dataset sizes? Scientific challenges for this exciting PhD project include: develop principled
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and democratic participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal
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under dynamic workloads, strict real-time constraints, and limited computational resources remains a key technical challenge. This PhD project addresses these challenges by developing efficient
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optimally for future challenges. This PhD position is part of the SecReSy4You MSCA Doctoral Network, which focuses on developing next-generation methods for security and resilience of cyber-physical systems
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develop personalised biofeedback methods that train youth and police to recognise subtle, often unconscious, signals of stress. It will enable target groups to react more adequately in stressful moments by