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to work on topics at the intersection of applied probability and analysis. The group around Pierre Nyquist currently consists of three PhD students and is focused on questions in probability theory and
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical
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collaboration with the group led by Asst. Prof. Gina Panopoulou. This includes code development, analysis and interpretation of data, writing manuscripts for publication and presenting work at relevant
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-related activities at the department (20%), including supervision of MSc and PhD students Possibilities for international collaboration and research exchanges Access to pedagogical training and development
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communication skills in English. Strong skills in programming and data analysis. Track record of scientific publications in international peer-reviewed journals. Meritorious qualifications include: Experience
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applications, specifically targeting the prognosis and risk prediction of Heart Failure (HF) in patients. This research integrates AI safety, explainability, and multimodal medical data analysis to enhance