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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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, letters of recommendation, etc). What happens next? The assessment of potential candidates is made primarily based on academic results from bachelor degree and master degree studies. Short-listed applicants
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the potential to accelerate materials design and optimization. By leveraging large datasets and complex algorithms, ML models can uncover intricate relationships between composition, processing parameters, and
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and empirically oriented, focusing on how political ideas, actors, and conflicts are shaped and mediated through digital platforms. Central themes may include, for example, algorithmic influence
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services. List of doctoral programmes and other offers Currently, eight structured doctoral programmes are part of the MMMIGS network: The CAUSE Research Training Group (Concepts and Algorithms For – and
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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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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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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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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have