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Field
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You
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of the North Sea. Existing automated detection algorithms will be used to identify seals and porpoises. The results will be used to create seasonal acoustic presence maps, investigate differences in community
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degradation modes. Evaluating suitable sensor technologies and data sources for acquiring relevant metrics. Developing tools and algorithms to automatically analyse sensor data, assess asset condition, and
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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but
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information from high-quality videos that share content with distorted footage as constraints in the learning process of modelling algorithms. This method uses the characteristics and knowledge embedded in high
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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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