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Field
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Systems (DESS) research group and supervised by Professor Torben Bach Pedersen. Within Digital Energy, DESS has developed the award-winning FlexOffer technology, one of the few open, general, and scalable
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | about 2 months ago
ecological questions. Your Tasks Develop and test novel forms of network-based feature selection for the application of ML algorithms to marine microbial eDNA and eRNA datasets, integrating a range of
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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strong background in scientific computing to contribute to various algorithmic patterns in an agile development environment. Within an Agile team set up: - You will contribute according to your expertise
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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs
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efficiency. Your Job: Develop and apply meta-optimization that can automatically search for the best algorithm-hardware pair Tackle the challenge of computationally expensive meta-optimization procedures by
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize
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. The goal is to develop a language-agnostic verification approach, following on promising results related to the Solidity language. - While our current digital infrastructure relies on classical networks
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, CU/DU/RU split). - AI/ML algorithms and methods for joint compute and radio resource management at the 6G edge leveraging accelerators - Control- and data-plane separation, real-time scheduling, and