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Field
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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-time sensing, multi-sensor fusion, and intelligent algorithms can jointly enable safer, greener, and smarter rail operations. Key research topics include eco-driving, environment cooperative perception
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should operate in an AI context. The AI revolution has sparked ongoing debates that highlight the multifaceted role of AI and algorithms in shaping our world—in ways that engage deeply with law. Fully
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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of ne computational chemistry algorithms in efficient computer codes • Demonstrated ability to approach complex problems creatively • Experience and/or interest in mentoring undergraduate
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of solvers for stochastic optimization problems, and test the methods on real-life data. As part of the PhD you will be following advanced courses to extend your skills, implement and test algorithms, and
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of peptide design and chemistry, computational methods (machine learning, deep learning, genetic algorithms), microbiology, synthetic biology, and related areas essential to developing novel