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Field
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processing and image representation Demonstratable experience in python for data handling and algorithm development Desirable : Knowledge and experience with imaging systems (X-ray CT, MRI or similar
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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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system perform well. This PhD project aims to answer this question. You will develop a unified mathematical theory and framework to study and explain how different reservoir systems work and how to design
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explainable AI for large-scale and complex datasets by developing algorithms, pipelines, and tools suitable for critical decision-making contexts. The doctoral student will be based at the Health Technology
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in underground facilities. The project aims to evaluate sensor technologies, design and optimize multi-sensor monitoring networks, and develop advanced detection and localization algorithms adapted
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of arrival (TDOA), angle‑of‑arrival (AOA), and frequency‑difference of arrival (FDOA) for RF emitter localization. Develops and implements signal processing algorithms and waveform prototypes using software
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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interface of machine learning, statistics, probability, and with applications in statistical genetics, developing new theory, algorithms, and scalable implementations. Starting date as soon as possible 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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consistent thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in