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Field
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sparse-regression based techniques to derive interpretable and computationally efficient differential equation models from computationally intensive multi-cellular agent based models (ABMs) of Epstein–Barr
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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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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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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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engineering or related fields. Candidates should have a strong research record in LLM-based agents, reinforcement learning, or large language models, preferably in areas closely aligned with the topics outlined
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an exciting approach to agentic, fully autonomous thin film development using a combination of automated electroplating, in-operando measurements, and AI driven algorithms. He or she will work with a team of
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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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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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Process: designing, preparing, shaping and characterizing materials in order to discover, control and optimize specific functions. The ICMCB carries out fundamental research on model materials and/or