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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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domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
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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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for computing performance guarantees of autonomous AI agents under uncertainty, which will be integrated to various degrees into a use-case with self-driving shuttles. Based on your experience and interests, you
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, computational biology, physics or a related discipline, and have experience of agent-based and/or continuum modelling, analysis and simulation. You will have experience of programming in Python and C
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of agent-based and/or continuum modelling, analysis and simulation. You will have experience of programming in Python and C++, or demonstrated ability to rapidly acquire fluent knowledge of new programming
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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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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