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- University of Warsaw
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the project is the development of AI-based pipelines for detecting, segmenting, and classifying lichen communities. Convolutional neural networks (e.g., U-Net, DeepLab) and machine-learning algorithms (e.g
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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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the Matlab and LabView environments for acquiring and analyzing measurement data, developing algorithms for criterion quantities for assessing the emission and propagation of conducted disturbances up to 150
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/undertaking dr hab. Szymon Toruńczyk Description of programme/project/undertaking The combination of methods from logic and graph theory has been extremely successful in the design of algorithms, in complexity
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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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conducting scientific research during the period of employment, i.e., to be included in the N number for the purposes of the base funding allocation algorithm for statutory activities. Specific Requirements
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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
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or equivalent Skills/Qualifications completed master’s degree in computational mathematics, fluency in Polish and English at B2 or higher level, ability to design and analyze quantum algorithms, ability to work
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developing measurement data processing algorithms; knowledge of lidar techniques; fluency in written and spoken English; efficiency in programming (MATLAB or Python) and ability to use MS Office, LaTeX