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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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vehicles capture videos or images for underwater pipes for inspection purposes. However, highly blurry or poor-quality videos can only be received under noisy environment. Therefore, developing accurate
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer
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education . Skills and personal qualities In addition to the aforementioned requirements for the position: A demonstrable computational competence, comfortable with using and developing algorithms, data
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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embedded within the department Law & Markets, home of a vibrant and diverse academic community. The overarching mission of the department Law & Markets is to develop and deliver cutting-edge, high-quality
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development over the last two decades. This research topic aims to define novel approaches to developing and combining these intelligences, utilizing both 1st and 2nd wave AI approaches, in the context
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, storage and demand. YOUR TASKS You will develop mathematical models and metaheuristic algorithms for complex optimization problems in the context described above, see e.g., https://arxiv.org/abs/2503.01325