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, semantics, functional relationships, and actionable affordances, and enabling predictive reasoning to bridge gaps when observations are missing or unreliable. As an optional extension, a learned world-model
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the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create interpretable, data-driven observers that enable physically grounded perception and control for robust
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explainable physics-informed RNNs for autonomous navigation and neural observer design within the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create
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biology, field- and experimental work, bioinformatics and statistical modeling. The successful candidate will apply cutting-edge genomic tools to disentangle ecological adaptation and spatiotemporal trends
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designing, developing and evaluating systems and models to enhance learning through AI technology. The PhD fellow will engage with developing and evaluating models and agents, as well as, multi-agent networks
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will develop models to understand non-equilibrium transport of orbital angular momentum in superconducting hybrid structures. This is part of an effort to determine the merits of superconducting
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of quantum condensed matter physics and has a duration of three years. Your immediate leader will be the Head of Department. Duties of the position The candidate will develop models to understand non
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regulations that provides both incentives and constraints for the maritime energy transition and emission reduction. The research objective of the PhD is to develop models that capture the interaction between
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? No Offer Description Simula UiB (https://simula-uib.com ) is a research institute in Cryptography and Information Theory located in Bergen, Norway. The Department of Information Theory is currently
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seasonal emissions such as winter CH4 emissions, using AI tools to develop upscaling tools or upscale to circumpolar region, or using climate modeling such as the Norwegian Earth System Model to constrain