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Field
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at the Institute of Visual Computing, course on Fundamentals of Geometry Processing, or Data Structures and Algorithms. Co-supervision of bachelor and master thesis. Research and development
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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network aims to deliver fiber-optic quality experiences over wireless links by building the theoretical, algorithmic, and architectural foundations of THz systems. It introduces ultra-MIMO (multiple-input
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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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to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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is not a standalone concept and has close connections to diversity, transparency and bias. In this position, the PhD candidate will work on algorithmic fairness in job recommender systems
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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control and reinforcement learning supported by an edge-cloud-based wireless communication environment. The doctoral student will work on data-driven theory and method development in simulation environments
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize