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fully funded PhD position in the area of safe data-driven system identification for cyber-physical systems, offered by our research group at the intersection of control theory, machine learning, and
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work • Experience in insect identification • Strong skills in the analysis of ecological data • Good command of the English language (C1), knowledge of German is of advantage • Good communication skills
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for RNAi and CRISPR reagent identification and off-target prediction (E-RNAi, E-CRISP), and public databases of functional screening data (GenomeRNAi, GenomeCRISPR), which are also part of the de.NBI and
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for RNAi and CRISPR reagent identification and off-target prediction (E-RNAi, E-CRISP), and public databases of functional screening data (GenomeRNAi, GenomeCRISPR), which are also part of the de.NBI and
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, clustering, neural networks) for spectral interpretation, segmentation, and material identification. • Create and curate a dedicated HSI spectral library for cultural heritage materials, linking reference