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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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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
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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historical and cultural issues. In addition to that, particular emphasis is placed on theories and approaches of modern literary studies and linguistics. Topics and methods in the digital humanities and
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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courses and transferable skills; support for attending conferences to present your work; an international graduate program in one of Europe's most exciting cities; financial support to learn German
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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the application of molecular biological methods experience in the statistical analysis of research results or willingness to acquire such experience very good knowledge of MS Office, including Word, Excel and