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innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top scientific research, we push back boundaries and
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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aims to develop responsible transport appraisal methods that consider multiple performance metrics simultaneously, with a special emphasis on fairness to weigh different circumstances, constraints, and
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on preferences the candidates will work along one (or more) of the following different directions: theoretical foundation involving quantitative models (e.g. stochastic, timed weighted, hybrid automata) and logics
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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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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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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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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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. -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