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Field
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in AI: Generative Diffusion & 3D/4D Scene Synthesis: Re-design diffusion and NeRF-style models so multiple agents jointly reconstruct a scene. Semantic-Aware Compression & Network Information Theory
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are collaborating in ScaDS.AI on advancing a broad spectrum of AI. The spectrum of available topics ranges from core areas of AI Theory, Hardware, Mathematic foundations, AI applications to societal aspects of AI
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pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
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theory for liquid crystal flow as well as theory for viscoelasticity of polymeric liquids. Both in the practical and simulation/theory work you will be guided and supported by post-docs and senior
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, classical ecological theories and methods to mathematically model species interactions networks and communities across spatial scales. As part of the project, the student will extend these methods and make
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, and theoretical analysis using Leslie-Ericksen theory for liquid crystal flow as well as theory for viscoelasticity of polymeric liquids. Both in the practical and simulation/theory work you will be
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large-scale MD simulations, ideally with LAMMPS, demonstrated via corresponding roles in publications Experience with density functional theory (DFT) calculations, ideally with VASP, demonstrated via
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Description Join us in seeking exciting new developments using graph theory in nearest neighbor models for active matter! Do you enjoy working with graph theory, and seeing how functions on graphs can inform
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geometry, enumerative geometry, and representation theory. Applications will be reviewed on a rolling basis until the position is filled. Early applications are strongly encouraged. The successful applicant
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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic