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Field
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Not required, but helpful: Experience with biomedical data/algorithms An affinity for applications of technology Contributions to open source projects This is what we offer A temporary contract for 38
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algorithms for resource-efficient hydroponics and evidence-based frameworks for integrating green space exposure for improved student wellbeing. This project will potentially enhance urban food resilience
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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of approaches based on algorithms, artificial intelligence and other analytical methodologies in the processes of detection, stratification, monitoring and communication of risks related to medicines and medical
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unit and then pre-processed data used as the input of the deep learning algorithm. The research will employ the SafeML tool (a novel open-source safety monitoring tool) to measure the statistical
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, the project will develop algorithms for ecological sensing, adaptive motion planning, and energy optimisation under real-world constraints. Scaled experiments and high-fidelity simulations will validate system
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will be an asset. The PhD will be supervised by Professor Helene Friis Ratner and conducted as part of the Algorithms, Data and Democracy project, founded by the VELUX Foundations. For more information
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experimental testing. You’ll design and run experiments, write and train algorithms, and contribute to open-source tools that may one day become industry standards. This project offers the freedom to explore
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@nhh.no AI and the Professional Services – Rethinking Structure, Strategy, and Work in the Age of Algorithmic Expertise Within DIGs AI agenda we have a particular interest in proposals linked to AI and
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Machine Learning. Work plan: Review of the state of the art on Evolutionary Algorithms and image tampering detection; Implementation of an evolutionary algorithm for image tampering detection