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Field
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, AI risks remain difficult to identify and assess. Many arise not only from technical limitations but from interactions among algorithms, users, workflows, and clinical environments. This requires
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, including user interfaces and algorithms, through participatory approaches that actively involve stakeholders (e.g., technology designers and actors from the public and private sectors). This approach aims
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-edge academic insight with real-world robotics applications. The PhD project will focus on the design of advanced control and decision-making algorithms to enhance the intelligence, autonomy, and
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pooling coordination schemes for CF-based 6G RANs. His/Her work will adress objectives like: (i) develop low-complexity ML algorithms for efficient multi-objective network optimization, radio resources
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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region of Portugal, although other tasks may be considered according to the profile of the recruited researcher. The researcher will be responsible for implementing spatial analysis algorithms, developing
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dynamic systems, control engineering, and applied mathematics? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead of time-consuming simulations to evaluate scenarios for improving the user experience along cycling and
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling