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-of-concept for a groundbreaking real-time dose verification system which is adaptable to different proton therapy treatment systems. This proof-of-concept detector system will be tested under
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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centres on natural science disciplines, particularly meteorology, emerging sensor technology, citizen science, and the development of early warning systems for location-specific natural hazards
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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additional year of teaching duties, depending on the applicant's competence and teaching needs of PSI. The planned start date is September 2025. The goal of LCBC is to understand differences and changes in
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to societal challenges Value conflicts and tensions in the life sciences and its different epistemic cultures and evaluative principles and practices. Applicants should read and relate to the more detailed
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our understanding of mental disorders by applying novel analytical tools to differences in genotypes and environment to predict disease trajectories. The project is part of a Nordic initiative in large
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equal, diverse and gender-balanced is essential for us to achieve our goals. We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem