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well as topics in phylogenetics. This project will involve working closely with experimentalists, and will be co-supervised by Prof Gerald McInerney and Dr Daniel Sheward, who have expertise in virology and
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’, i.e. policies that deal with problems after they occur, rather than long-term prevention. By developing innovative simulation models that incorporate the life-course consequences of policy options, your
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to you, we will consider together what your needs are, and draw up a development plan. This position is a good fit for you if you recognise yourself in the following: A (Research) Master’s degree in
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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diseases, and how these influence, or are influenced by, labor force participation and income. In addition, you will develop simulation models to predict how different policies could reduce the disease
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position is available at the Department of Pharmacy , Faculty of Health Sciences , within the Microbial Pharmacology and Population Biology (MicroPop) research group , led by Prof. Pål J. Johnsen
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, analysis, and model choice while retaining strong error guarantees. This means that researchers can adapt their research questions and sampling plans to the data as they come in and in a way that is as model
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leader will be the Head of Department. About the project Modern control systems rely on being at least partially predictive while digital twins also must maintain a state model of the targeted cyber
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application - please check your spam folder] More information: Prof. Kim Calders | kim.calders@ugent.be