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contribution of genetic and non-genetic driving forces for the cells’ evolution and glioma development. Using multi-omics data integration and machine learning, we will investigate cellular behaviors and gene
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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are in engineering sciences, mathematics, computer sciences, natural sciences and medicine. Our economics, social sciences and humanities are indispensable and crucial disciplines in a modern university
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Curriculum and other under and post graduate degree programmes that involve the Faculty of Medicine. Further, they will be expected to teach in areas outside their specialisation. The successful candidate will
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Associate Professor of Experimental Physics Focusing on AI-Based Research of Biomolecular Structures
obtained and to solve complex macromolecular structures, the development and use of artificial intelligence and machine learning will increasingly be required. FAU and HZB are jointly appointing a
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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in high-performance computing, materials chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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terrestrial system models, for example using data analysis methods, such as data assimilation, physical- or process-based machine learning, or deep learning algorithms Analysis of the effects of human