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of this PhD project is to develop novel 4D image reconstruction methods for X-ray imaging where the object changes over time. In particular, the goal is to develop efficient 4D reconstruction algorithms
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-precision localization and radar-based sensing. You will develop adaptive algorithms that dynamically select the optimal radio configuration based on the specific requirements of each application. The radio
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large datasets. Proficiency in Python, MATLAB, or similar platforms used for image analysis, data modeling, and algorithm development. Experience with environmental analysis or microplastic research is a
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machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in
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PhD working with Prof. Hendrik Blockeel and/or Prof. Jesse Davis on analysis of time series data. The goal is to develop algorithms for detecting anomalies, discovering “motifs” (repeating patterns
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collaborations with industrial partners as well as national and international academic initiatives. These projects span the full research and development lifecycle, requiring large-scale experimentation, real-time
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independent research and develop novel algorithms. You have strong analytical and problem-solving skills. You have a research-oriented mindset and motivation to work at the intersection of AI and communication
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flexibility for the PhD researcher to develop their own research ideas, and that plans or topics may evolve based on advancements in academic literature or emerging opportunities. Nonetheless, the primary
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Economics » Cyclical economics Economics » Econometrics Economics » Economic policy Economics » Economic systems Economics » Economic theory Economics » Economics of development Economics » Environmental
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project focuses on developing ultra-reliable spatiotemporal (4D) predictions using trustworthy, distributed AI-driven intelligence deployed across heterogeneous aerial nodes. To achieve this, an aerial