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, techniques and the research basis for a portable AI-based, marker-free 3D modelling system to generate personalized avatars. We utilize recent advances in programming tools for hybrid physics-AI problems and
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on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of molecular data in cancer genomics. Emphasis will be placed on rank-based models and their
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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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build a CRISPR-based gene editing platform that can correct patient-specific mutations in ex vivo cell therapies for genetic immune diseases. We focus on correcting blood stem cells for curative therapy
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replacement in Eastern Asia, a key but understudied region in the ‘protein transition’. Focusing on a range of meat replacers, such as plant-based meat analogues, insects and lab-grown meat, the project focuses
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transition’. Focusing on a range of meat replacers, such as plant-based meat analogues, insects and lab-grown meat, the project focuses on the entire region but zooms in on two key but highly different case
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childbirth. Data from Norwegian and Swedish observational cohort studies (NOWAC, SCAPIS) and randomized clinical intervention trials in lactating women will be used. The position is based at the Department
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for mental health issues based on their genes and environment. The tools and data created will be shared to help other scientists study and address these important issues. The position(s) will be
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the University’ Centre for Global Sustainability, Institute of Health and Society and Department of History. They will be based in the interdisciplinary Global health politics research group at the University
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independently. Well-organised and able to structure own work. Ability to think creatively within a scientific framework. Employment in the position is based on a comprehensive assessment of all qualification