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, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations
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PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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: Data Mining Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology