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try again. UiO/Anders Lien 11th May 2026 Languages English English English PhD in Generative AI and Statistics: Coalescent-inspired diffusion models for discrete data Apply for this job See
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for complex models, causal inference and survival models, measurement uncertainty, and research for clinical trials and observational studies - and numerous collaborations with leading bio-medical research
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, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging
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interpretable framework for tensor analysis. Specifically, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for
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who are motivated to explore complex questions at the intersection of health, economics, and policy What Makes HEPARD Unique? International and Interdisciplinary Training: Benefit from a unique
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novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging, and clinical
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disciplines. We welcome candidates with strong academic backgrounds in economics or related fields who are motivated to explore complex questions at the intersection of health, economics, and policy What Makes
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are motivated to explore complex questions at the intersection of health, economics, and policy. What Makes HEPARD Unique? • International and Interdisciplinary Training: Benefit from a unique opportunity to
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Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions in the T-PRESS Evidence Ecosystem Framework”. The primary objective of the T-PRESS consortium is to
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, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling. The centre has numerous collaborations with leading biomedical research groups internationally and in