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. The successful candidate will be based in Odense, under the primary supervision of Prof. Ricardo J. G. B. Campello , but they will be expected to also work closely with other PhD students, postdocs, and
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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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approximation algorithm, using linear programming methods. Over the next years, the project will grow to a collaborate team of 4-5 PhD students and Postdocs. The successful candidate will work directly with the
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Administrator, an Administrative Supporter and approximately 10-15 PhD students, postdocs, and visiting scientists. Several POLIMA researchers have attracted prestigious personal grants, e.g., Villum Investigator
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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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professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with the University of Leipzig (Bioinformatics, Prof. Peter Stadler
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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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active within the following areas: Probabilistic assessment of structures and structural elements. Including focus on uncertainty modelling of structural models and load models. Derivation of optimal
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CMOS analog/mixed-signal circuits (Cadence, Spectre, etc.) Optimize circuits for power, noise, and area constraints Prototype and validate circuits with EEG signals and wearable sensors Collaborate with