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teaching hospitals, the department works closely with clinicians and other research groups to ensure strong translational impact. Its mission is to revolutionise healthcare through data‑driven modelling
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At the University of Vienna more than 11,000 personalities work together towards answering the big questions of the future. Around 7,700 of them do research and teaching, around 3,000 work in
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manufacturing. AI methods will then be applied to this large database to inform optimal processing parameters that will produce components with reliable material properties. The process will be validated in a
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polymers, using additive manufacturing. AI methods will then be applied to this large database to inform optimal processing parameters that will produce components with reliable material properties
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and analysing health data e.g., electronic health records, and/or satellite-derived data analysis products and GIS data as well as experience in medical large language models and foundation models e.g
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” research themes. The successful candidate will have: a PhD in Translation Studies/Machine Translation; practical experience conducting data-driven research in a machine translation/large language models (LLM
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. Experience with machine‑learning interatomic potentials and their deployment in large‑scale molecular dynamics simulations. 2. Experience working in multicultural and international research environments
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computational methods for analysis and interpretation of large-scale biological datasets. Experiences in structural homology modelling is not essential but would be advantageous. The post holder will work in a
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other RAs, the PDRA will lead the collection, management and analysis of large physiological, fMRI and behavioural data sets, using appropriate tools (R, Matlab, FSL, SPM) and advanced statistical
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large