46 algorithm-development-"Multiple" PhD scholarships at Technical University of Munich
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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. The project focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how
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full-time PhD candidate on the topic of “Automatic Recognition of building attributes” About us The TUM-Professorship for Data Science in Earth Observation develops innovative methods for information
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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developing NLP applications. Proficiency in Software Engineering and Data Science techniques. High motivation to create innovative NLP solutions addressing business, medical and societal needs in collaboration
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political and economic power, geopolitical and distributional conflict, or institutional legacies and influential ideas shape how and which technologies are developed and deployed - and how this in turn
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/Materials Science funded by ERC StG with excellent opportunities for both research and career development. About us Our research focuses on extracting and isolating bio-based polymers such as cellulose and
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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to be developed. One promising research direction is the use of physics-informed deep learning, such as physics-informed neural networks or deep neural operator networks. Tasks: Work in a team on national
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regeneration in the forest interior“we aim to develop innovative remote sensing approaches to enhance the mechanistic understanding of the effects of increasing forest disturbances on closed canopy forests