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atmospheric delay correction for spaceborne GNSS-R. As part of the GRS Laboratory, the PhD candidate will contribute to the development and implementation of cutting-edge deep learning techniques for space
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and its audience responses. While a separate PhD project will focus on the international reception of FoM, the PostDoc research is intended to study the heritization process of Edward Steichen in his
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order of 5 ECTs on specialized topics, close to a given DC personal project, to allow him/her to acquire a deep understanding of her/his subject. Second, the network-wide training will be offered by
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degree in computer science or related discipline Strong interest in applied machine learning, including but not limited to deep learning Strong interest in image analysis / computer vision and pattern
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personal project, to allow him/her to acquire a deep understanding of her/his subject. Second, the network-wide training will be offered by the consortium during the whole project life cycle through 4
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leverage satellite communication, IoT and deep learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction
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, such as the University of Liège and Aachen University, is anticipated. Your Profile The expected PhD candidate should have: A Computer Science background Expertise in Machine Learning, Deep Learning
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... The expected PhD candidate should have: A Computer Science background Expertise in Machine Learning, Deep Learning Good programming skills (python, Java…) Fluent written and verbal communication skills in
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for promoting the institute’s/sector’s reputation internationally, nationally and locally across scientific and policy-making communities. Your profile-PhD degree in one of LISER’s main expertise area;-Experience
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colleague? Apply now! Education PhD in Electrical Engineering, Energy Engineering, Economics or related fields, with specialized expertise in business models and market dynamics within energy systems