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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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Experience with performing laboratory experiments Ability to work with large data sets (> 500 GB) Numerical modelling Main responsibilities Independent research and research training (80% of time) Support for
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) workflows for learning from large-scale imaging and molecular data Develop ML models to investigate cellular responses, particularly in cancer cell lines Develop DL models for molecular design based on time
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methods when limited data is available. Large neural networks are known to be heavily inefficient in this limit, and we aim to discover better methods for this purpose. We would like to study how prior
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, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence
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in a large project rather than on your own in a single project. The following experience will strengthen your application: Experience in energy storage, organic synthesis, or materials characterization
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construction. Information about the research environment The PhD student will join the research environment Architecture, Media, and Material Practice (AMMP) at the Department of Architecture and Civil
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum