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Modelling ore fabrics along comminution to predict liberation. Your tasks Develop a methodlogy to predict breakage and liberation, including: Develoment and implementation of parametric, fast preferential
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Information Processing Systems, 31. (2018). [3]. Höge, M., Scheidegger, A., Baity-Jesi, M., Albert, C., & Fenicia, F. Improving hydrologic models for predictions and process understanding using neural ODEs
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
-like AI models which can predict DNA structures Performing experiments for validation Participation in conferences in Germany and abroad (incl. presenting your research results) Preparing scientific
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training data Building transformer-like AI models which can predict DNA structures Performing experiments for validation Participation in conferences in Germany and abroad (including presenting your research
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to facilitate a rapid and efficient exchange among experimental and computational groups and Devise an approach in invertible predictive modelling that links semiconductor properties to the composition of lead
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Prediction of metabolic activity in complex microbial communities, leveraging
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Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
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management platform that connects institutes to facilitate a rapid and efficient exchange among experimental and computational groups Devising an approach in invertible predictive modeling that links
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: Approximately 2,000 EUR/month for three years Website: IMPRS-ESM Application Contact: office.imprs at mpimet.mpg.de The International Max Planck Research School on Earth System Modelling (IMPRS-ESM) invites
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and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover