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systems, including their reliability and resource efficiency during production and operation. To support our team, we are looking for a working student in the field of “Classical and Quantum Computing
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) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and
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computational analysis, including algorithm development, will be integrated throughout the program. Managing collaborations with other research programs within and outside of the lab will be necessary
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the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy Materials and Devices – Structure and Function of Materials (IMD-1) to establish a data-driven
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on primary human samples derived from blood or tissues in individuals with characterized infection or tumor histories. Using a combination of bioinformatic and computational approaches, we will integrate
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algorithms in statistics and machine learning Type of programme/project/ undertaking MAESTRO-16 Funding institution National Science Centre (NCN) Duration of programme/ project/undertaking 09.04.2025
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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Power Engineering • Relevant experience in power electronics, wide band gap semiconductor devices, multilevel inverters, soft-switching high-frequency power converters, drives, control algorithms