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on the solid application of scientific research method. The department has a pluralistic approach to research methods that includes, for example, formal theoretical models, quantitative empirical methods such as
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deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine which features are relevant? These questions
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or energy-efficient mission execution. Similarly, advanced control algorithms depend on reliable sensor integration and accurate dynamic models of the vehicle and propulsion system. The PhD project will
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. The project involves the development and modelling of hydraulic systems, with particular emphasis on energy-efficient system architectures and appropriate component selection. A key aspect is to incorporate
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and structure of healthy anatomy and detect any deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine
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-Physical Energy Systems The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be designed and deployed efficiently
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to develop and validate models for evolutionary and ecological hologenomics at the Center for Evolutionary Hologenomics, GLOBE Institute, University of Copenhagen. Our group and research The Center
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Learning models to understand and predict interactions in dynamic ecological networks. Our lab is looking for candidates for the following stipend: Learning the Structure and Dynamics of Complex Networks We
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whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at