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background in mathematical optimization and development of algorithms would be considered an advantage. You are experienced in conducting independent research and highly motivated to develop mathematical
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usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and algorithms for resource-efficient
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in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses on methodological development in cryo
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positions in the interdisciplinary research environment “Culture and Society” to develop research on themes relevant to the thematic area “Digital Society, Infrastructure, Legacies”. This thematic area
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methods that reduce compute, energy usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including
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. The role involves contributing to this research project with a focus on model development, implementation, and testing. Further tasks involve dataset curation, analyzing results, and the creation
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research within Unmanned Traffic Management (UTM). In this role, your primary responsibility will be the hands-on development of advanced simulations and prototypes that help us test and validate new UTM
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes