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applications, where we have to deal with detailed and large-scale datasets, often coming from a variety of sources ranging from traditional CAD modelling to 3D scanning. The aim of this research position is to
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model without sharing their personal data; FL reduces data collection costs and protects clients' data privacy. In doing so it makes possible to train models on large datasets that would otherwise have
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methods to accelerate the discovery and optimization of novel materials, and actively develop large-scale materials models (AI for Science) to transform the R&D process through AI-driven paradigms. In
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) GRADE 7, £39,355 - £45,413 pa Fixed-term Ref: 095593 A Research Fellow position is available in the group of Professor M. J. Rosseinsky OBE FRS to work in a team of computer scientists and materials
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descending systems in the brain convey information to the spinal motor system, and define the functional roles of spinal interneurons in generating behavior. This position broadly focuses on understanding
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Associate Professor or DTU Tenure Track Assistant Professor (junior group leader) in High-through...
to implement standardized experimental protocols, harmonized data formats, and transparent documentation practices—laying the foundation for reproducible and collaborative research in biofertilizer innovation
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transcriptomics) opens new research horizons on cancer pathologies. These data, of very large dimensions and volume, bring new methodological challenges in terms of statistical and mathematical analysis, as
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of the position is 1 August 2026, or as soon as possible thereafter. The QM centre is located at the Faculty of Science on the international campus in Odense, Denmark and it is hosting several large European
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of the position is 1 August 2026, or as soon as possible thereafter. The QM centre is located at the Faculty of Science on the international campus in Odense, Denmark and it is hosting several large European
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Cloud project. This position plays a pivotal role in driving the success of multiple applications designed to facilitate large-scale pediatric cancer data sharing, research collaboration, and data