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Field
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scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making
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trends, and their future developments come with deep uncertainties. Infrastructure policies must account for these uncertain drivers and their dynamic interaction with changes in intended use. As part of
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large-scale neural models of the early visual system. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience and strong deep learning
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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on the use of new Lyapunov-based deep learning methods. Such development includes: ideation, mathematical development, Lyapunov-based analysis, executing simulations and experiments, and disseminating research
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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communication skills an early career researcher with publication record, presentation skills and commitment to research integrity equipped with excellent software skills and hands-on experience with deep learning
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: You will be responsible for the sensor system and the perception algorithms of an autonomous mobile robot. You will engage in research around deep learning and 2D/3D computer vision for a well-defined
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
students with strong theoretical foundations and a desire to contribute to fundamental algorithmic research. Our group works at the intersection of algorithms, machine learning, and interactive visual
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participate in the creation of next-generation drug discovery platforms for AMD. The successful applicant should have research experience in at least two of (a) deep learning and AI methods; (b) causal search