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Field
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, immunology, and allergology to better understand the interaction between airway epithelium and mast cells within healthy and diseased airways, identify biomarkers, and develop algorithms for the diagnosis and
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management systems (BMS). Ability to develop and implement algorithms for modelling, estimation, or control applications. Strong analytical thinking, problem-solving ability, and capability to conduct
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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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systems with "self-diagnosis" and "self-healing" capabilities. By integrating federated learning, graph neural networks, and blockchain technology, we will develop a framework that moves beyond static
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to the academic development of the Programming area within the Programme and participate in high-quality research activities in areas related to theoretical computer science, algorithms, data structures
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tomography and local adaptive reconstruction to overcome these challenges. Your tasks develop physics-informed, self-supervised learning approaches for phase retrieval implement reconstruction algorithms
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reconstruction to overcome these challenges. Your tasks - develop physics-informed, self-supervised learning approaches for phase retrieval - implement reconstruction algorithms on HPC clusters for large-scale
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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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both individual decision-making and multi-agent cooperation. The student will investigate two complementary directions: ToM-Enhanced Decision-Making for Autonomous Agents: Develop decision-making
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques