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Field
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the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and
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genomic approaches Application of the modeling approaches in relevant downstream tasks Co-development of high-performance computing AI training codes for the first European Exascale Supercomputer JUPITER
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static and dynamic 3D reconstruction, semantic scene understanding, and generative models for photo-realistic image / video synthesis. Overall, the main focus is on high-impact research with the aim
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quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good communication skills in
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software
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18.10.2022, Wissenschaftliches Personal The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes