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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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of supporting the selection of aortic valve prosthesis using CFD simulation, machine learning and multi-stage validation, (2024/54/E/ST8/00100) Requirements: PhD in technical sciencesThe mandatory formal
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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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the project based on your interests and in collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a PhD
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You hold a PhD in Computer Science, Artificial Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep
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economic modeling, with interests including improved spatial resolution and machine-learning-enabled approaches for policy analysis. Postdoctoral Position (f/m/d) – Integrated Assessment Modeling (Climate
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and
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in IEEE Communications Society’s and IEEE Signal Processing Society’s journals and conferences. Strong background in communication theory, signal processing, machine learning, and optimization theory
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At the Technical Faculty of IT and Design of the Department of Sustainability and Planning, Copenhagen, a position as Postdoctoral researcher in Geospatial Machine Learning for Predicting Land Use