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Field
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shape the future through innovative education and ground-breaking research results, and based on the Arctic region, we create global social benefit. Our scientific and artistic research and education are
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the deployment of coordinated flexibility measures. The research topics to be addressed in the project are: How and to which extent can agent-based energy simulations, powered by AI-driven forecasts within a UDT
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/Project: We are building an optimisation-driven framework that (i) makes AI agents reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses
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in ecological fieldwork, ideally in wet grassland or agricultural systems - Skills in GIS, remote sensing, and spatial data analysis (bonus: agent-based modelling) - Demonstrated ability to work in
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either or both agent-based modeling and social network analysis/network science. The ideal candidate should be able to program in C or C and have experience working with tera-bytes of data. Preference
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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during verbal interactions with human and AI agents. You will be based within the Section for Cognitive Systems, which is a lively and research oriented group of scientists and support staff with a broad
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transplantation using mouse animal models. The research involves understanding the mechanisms underlying resistance/relapse following immunotherapy such as CAR T and developing novel agents for protecting
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, supply chain management, or a related field. Experience with system modeling or scenario analysis (e.g., system dynamics, agent-based modeling, MCDA, causal mapping). Understanding of or interest in
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is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial