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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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, bio-inspired amphibious robots design as well as AI application in vortical flow control and sensing. Based on physics-informed (and -informative) machine learning, we combine domain expertise (fluid
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, bio-inspired amphibious robots design as well as AI application in vortical flow control and sensing. Based on physics-informed (and -informative) machine learning, we combine domain expertise (fluid
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 16 days ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
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challenges in urban development. You will explore exciting areas such as applying machine learning models to analyze urban mobility patterns, identifying gaps in transport accessibility, and supporting
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systems), Mathematical biology (Dynamics of ecosystems, Animal movement, Epidemic processes, Forest fires, Biological evolution, Modeling based on Machine Learning and Neural Networks), Socio-economic
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on analysing modern and historical textual records through the lenses of graph-network analysis, statistics and machine learning. The topics include: * Topic: Networks in Historical Scholarly/Philosophical