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: Probabilistic generative models (VLMs, diffusion, flow models) Reinforcement learning & Markov decision processes Causal inference & counterfactual reasoning Mechanistic & physics-informed modeling Agentic AI
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metastatic sites, macrophages are key effectors mediating tumor immunosurveillance. Macrophage-based cancer immunotherapy is considered one of the most promising fields in cancer immunology and the next
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tool based on inverter data and digital twin models, enabling the correlation of string-level anomalies with module-level fault localisation. Validation of the integrated system in real photovoltaic
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project, aims to contribute to the development and preclinical evaluation of new platinum-, palladium-, and nickel-based anticancer metallodrugs, using metabolomics approaches based on Nuclear Magnetic
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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range of methodological approaches is relevant for the theme, including qualitative case studies, optimization models, system dynamics modelling, and agent-based modelling. Please note that the project
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Technology PhD programme: UiT - The Arctic University of Norway, Faculty of Science and Technology Starting date: preferably in 2026, by agreement Project 6: Multi-agent knowledge bases Employment: UiT
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: Multi-agent knowledge bases Employment: UiT - The Arctic University of Norway, Department of Physics and Technology PhD programme: UiT - The Arctic University of Norway, Faculty of Science and Technology
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hospitals. PRIMARY DUTIES AND RESPONSIBILITIES: The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration