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target investigations in biliary atresia. We are looking for a person with a relevant degree (MD, MSc. etc.) Research environment The PhD project will be based at the Department of Inflammation, Institute
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related to Riemann-Steltjes optimal control to combine PMP with Bayesian Optimisation, allowing for data-efficient learning. You will then implement and validate the new method on simulated fermentations
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environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will
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Bayesian Networks (DBNs) for probabilistic risk modelling Scenario-based simulation for rare-event analysis You will be part of a dynamic, interdisciplinary research setting at one of Europe’s leading
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statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will quantify and analyse uncertainties in the design and operational performance
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cellular receptors present in target species, where in the cells the virus is located and identify species dependent differences in disease development and receptor expression. Techniques employed will
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: Increased sorting More targeted handling of different types of waste Better control of hazardous substances (VCØB, 2021). Current research focuses either on either on reducing construction site waste or
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molecular photoswitches or redox-active cycloparaphenylene molecules will be targeted. Stepwise synthesis protocols for constructing elaborate target molecules need to be developed. The properties
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shape metabolic interactions, electron-transfer strategies, and functional specialization. You will run targeted experiments with defined methanogenic communities, compare ancestral and evolved consortia
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of the position will be 1 April 2026 or as soon as possible thereafter. Project background Amino acid transporters have been implicated as possible drug targets in a number of diseases such as notably cancer