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in process design and process optimization, including model development and numerical simulation (Matlab, Aspen etc.) of advanced adsorption processes such as TVSA and ESA (joule heating, inductive
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their power consumption, select the most appropriate options and dimension them optimally. This also supports the development of run-time control mechanisms maximizing the transceiver energy efficiency in
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, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and
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, Research Group Musculoskeletal Rehabilitation, we are looking for a part-time doctoral assistant, who will collaborate on a project concerning optimization of the guidance of young (elite) athletes
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sensing. You will develop adaptive algorithms that dynamically select the optimal radio configuration based on the specific requirements of each application. The radio platform supports a range of physical
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to support this in the most efficient way. Ultimately, deploying and optimizing different base stations types on different sites may require AI solutions to master the multi-dimensionality of related scenarios
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include nucleic acid extractions, Sanger sequencing, PCR assay optimization and RT-qPCR. This position offers the opportunity to work closely with a dynamic team of PhD students and postdoctoral researchers
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solutions. You may also consider hybrid solutions such as combinations of optimization-based MPC with data-driven RL methods. You use the aforementioned AI techniques to research scalable/distributed
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based on extensive and realistic end-to-end simulations, and optimize them for the best performance/complexity trade-offs. By doing so, you will enable hybrid PHY implementations combining traditional and
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compounds via microbial cell factories and synthetic biology (WP3). These plant-AMF signaling compounds are essential for optimal fungal colonization of the plant roots. They will be identified by other