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Field
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between objects. A common way to represent a graph is to use the adjacency matrix associated with the graph. However, adjacency matrices only model networks with one kind of objects or relations between
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to identify metabolic response patterns and develop predictive models for personalized nutrition. Supervising master’s and/or doctoral students to a certain extent Possibility to engage in teaching at
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage
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: you will divide your time in equal shares between teaching GISc at bachelor and master levels, and advancing research about the integration of statistical movement models with predictive simulation
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methodology, as well as applying it to the development of a data-driven model for climate prediction of the El-Nińo-Southern Oscillation. This project has recently been funded by the Australian Research Council
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. The Postdoctoral Associate will work under the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB
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computational methods to address and derive theoretical models and predictions. For this line of research we are seeking several postdoctoral researchers to work synergistically both within the team and with our
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Shell Model with Continuum and its extensions to construct high-fidelity microscopic optical potentials, designed for use in few-body reaction formalisms, in particular Faddeev-type calculations targeting
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of solid sorbents. Sorbent modelling and prediction of performance or ageing. Our offer We offer a stimulating, international, and collaborative research environment at a leading research institution with
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental