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how prophages spread and impact host fitness without interference from background MGEs. All this will be modelled and simulated in silico, and model outcomes will be further validated in the laboratory
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preferably has strong programming skills and experience with the modeling and simulations of fluid or solid mechanics or ice sheet flow and deformation (for example by use of finite element/volume methods
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candidates within the field(s) of biology, biochemistry and molecular biomedicine or similar. We are particularly interested in applicants with strong prior knowledge of pancreatic cancer biology, tumor
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of computational chemistry. Applicants can have a background from cheminformatics including RDKit, machine learning applied to chemistry, and molecular modeling Our group and research- and what do we offer? Our
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optics and/or atomic, molecular and optical physics. We are looking for applicants who have: Experience with using and building optics/lasers (important). Experience with atomic physics and laser
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disease. We develop supervised, un-supervised, self-supervised and generative models to learn across multiple types of data rather than treating each data modality in isolation. We have a high focus on
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of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process
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tools from chemistry and biology, and apply these in studies of therapeutic peptides and proteins. Our aims are to develop modulators for protein-protein interactions (PPIs) and to provide molecular-level
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to the PhD project ie. processing and analysis of dietary intake data, statistical analyses (eg. linear mixed models) as well as evaluation of child growth and body composition data. Relevant publications
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delivering influenza vaccination through intramuscular and intranasal routes, which will be compared to a live influenza human challenge infection model in humans. Methodology will involve implementation