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Field
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education, research, or knowledge-intensive industry. The position reports to the Unit Leader of Colorlab. About the project The research will address the growing need for reliable methods that can assess the
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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-content microscopy and AI/deep-learning-supported image analysis will be used to quantitatively assess neuronal morphology and maturation. Parameters will include dendrite length and branching, axon growth
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reconstruction and analysis. Turn novel research algorithms into robust tools that can be used by scientists beyond the original developers. Design APIs and workflows for both rapid internal research and reliable
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. The team specializes in multi-sensor methods, tensor decompositions and component analysis for the joint processing of multimodal data, notably in the context of invasive (intracardiac electrograms) and non
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on electrical and calorimetric efficiency measurement has the primary emphasis of: measurement-system design, sensor characterization, uncertainty analysis, converter testing and calorimeter development. The best
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, analysis, visualization, and data interpretation for patient stratification, discovery of biomarkers for disease risks, diagnosis, drug response and monitoring of health. The precision medicine research is
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of the developed formulations; analysis of relationships between the properties of the developed formulations, the mechanisms of action of their active components and the observed biological effects; participation
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scientific initiative focused on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and
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in order to recruit 11 outstanding PhD students. The MoM section is recognized worldwide for its high-level research on experimental analysis, theoretical understanding and predictive modelling