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Field
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interdisciplinary research, integrating molecular simulations, machine learning, statistical physics, multiscale modeling, and uncertainty quantification. By integrating state-of-the-art machine learning models
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? You are studying Mechanical Engineering in the field of Aviation or Shipping. Do you have knowledge of design and machine elements? Are you proficient in CAD and maybe even have first experiences in FEA
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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with other research groups for chip applications, e.g. in physics, life sciences, materials sciences, medicine, and machine learning. Chip Design is also a focus of the Master′s program in Computer
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transmission schemes, protocols and cross-layer optimizations for contributing to relevant standardization bodies Implement prototypes involving machine learning techniques to optimize for latency, reliability
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on the available topics and the competencies and interests of the student. What you will do The goal of the thesis is to perform state-of-the-art research in computer vision and machine learning for biometrics
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), and computational modeling (deep neural networks). We apply multivariate analysis methods (machine learning, representational similarity analysis) and encoding models. Job description: This is an open
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, innovative research program particularly in the field of systems immunology applying novel high-resolution technologies, and/or computational analysis methods and artificial intelligence/machine learning is
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-driven energy systems research – scalable, transparent, and interoperable. Your tasks in detail: Development of a structured description format for the unambiguous and machine-readable characterization