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of advanced modelling and machine learning methods, and may involve the following areas: Dimensionality reduction. Data-driven methods for estimating dynamical models Data-driven methods for estimating
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developments in agentic AI. This means that you are expected to stay up to date with research on LLM-based agents, prompting methods, fine-tuning strategies, and multi-agent systems, and to assess how
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have been completed earlier. Additional requirements: Very good oral and written proficiency in English. Demonstrated experience in computational methods, particularly in deep learning and computer
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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streams, contributing to elevated environmental mercury levels and increased human exposure. It is estimated that around 300 tonnes of mercury are released annually through these processes, making them one
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will be as a researcher in a two-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault
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increased human exposure. It is estimated that around 300 tonnes of mercury are released annually through these processes, making them one of the top three sources of anthropogenic mercury emissions worldwide
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-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault diagnosis of gas turbines
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communication networks using AI-powered methods. We will advance the research front in defending future generation networks by: prevention of cyberthreats through anticipating and mitigating them, accurate
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agents, prompting methods, fine-tuning strategies, and multi-agent systems, and to assess how such methods can be incorporated into the project’s empirical and theoretical work. The position is therefore