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to machine learning and artificial intelligence is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must be
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. Familiarity with research relating to machine learning and artificial intelligence is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative
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will also be encouraged to take part in the supervision of MSc and PhD candidates. You will be part of a larger project group across robotics, machine learning and health, and also interact with
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to data-driven (machine-learned) representations. In particular, we are interested in the joint applicability of such models and to what extent simpler models (possibly based on machine learning) can be
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-performance computing, via reduced-order models to data-driven (machine-learned) representations. In particular, we are interested in the joint applicability of such models and to what extent simpler models
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, and applicants must also have a specialization in bioinformatics, machine learning/artificial intelligence, simulation/visualization, dynamic systems, or signal processing/computer science, or have the
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at the same level, and applicants must also have a specialization in bioinformatics, machine learning/artificial intelligence, simulation/visualization, dynamic systems, or signal processing/computer science
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fields both locally (field by field) and regionally (groups of fields). Data driven analyses will be complemented by physical reservoir modelling, with machine learning approaches to extract correlations
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on the expertise of the seven research groups involved, using a combination of experiments in cellular and animal model systems, mathematical modelling, machine learning and music technology. One PhD student
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1st August 2024 Languages English English English The faculty of Technology, Natural Sciences, and Maritime Sciences has a vacancy for a position as PhD Research Fellow in “Hydrogen and ammonia