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, current methods are either static, rely on heavy offline training, or fail to adapt to changing environments. This PhD project will develop intelligent software agents capable of autonomously optimizing
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for the green transition of the energy sector. Our research develops innovative digital tools and methods, combining cutting-edge AI, simulation, and optimization, to create smarter, more resilient, and
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems
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to optimize performance and interpretability, analogous to RAG (Retrieval-Augmented Generation) in LLMs Investigating multiple models for analysis, focusing on the Occam’s Razor principle of preferring simpler
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for assessing and improving the performance of existing structures. The position is to be filled by February 1, 2026, or as soon as possible thereafter. Job Description The successful candidate will be part of