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surrogate models. The method employs modern posterior sampling algorithms, using measurement data. The developed tools will enable faster and more accurate reconstruction of past and future emergency events
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environments for acquiring and analyzing measurement data, developing algorithms for criterion quantities for assessing the integration of distributed generations with the power grid, developing data preparation
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analysis algorithms will be used to assess how different neutrophil subpopulations directly and indirectly kill tumour cells, and how this behaviour is influenced by other cells in the tumor microenvironment
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skills in designing advanced neural networks (including Vision Transformers, Graph Convolutional Networks, and Spiking Neural Networks), hardware implementation of algorithms for reconfigurable FPGA
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or equivalent Skills/Qualifications The post-doc is expected to independently design, plan and conduct experiments. In addition, will oversee the work of the PhD student. Responsibilities: -To develop algorithms