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to peer-reviewed journals. The role holder will have the opportunity to use their initiative and creativity to develop research methods and extend their research portfolio. Both positions are full time and
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/unsupervised learning (regression, classification, clustering), ensemble methods, and deep learning architectures (CNNs, RNNs). Experience with explainable AI (e.g., SHAP, LIME) and radiomics preferred
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will have the opportunity to use their initiative and creativity to identify areas for research, develop research methods and extend their research portfolio Candidates must hold a PhD, or be near
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, interpret and evaluate research findings/data using approaches, techniques, models and methods selected or developed for the purpose. - To establish a national reputation and regularly disseminate and explain
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methods. Ability to assess and organise resource requirements and deploy effectively. Ability to build relationships and collaborate with others, both internally and externally. Some practical experience
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, models, techniques and methods. Ability to assess and organise resource requirements and deploy effectively. Ability to build relationships and collaborate with others, both internally and externally. Some
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opportunities for people traditionally under-represented in mathematical education research and to enabling everyone to flourish. You must have expert knowledge of quantitative research methods and statistical
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workshops, methods training, joint stakeholder sessions, and work-in-progress presentations. The Centre's ECRs will work as teams on specific projects. The role-holder will also collaborate with ECRs based
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workshops, methods training, joint stakeholder sessions, and work-in-progress presentations. The Centre's ECRs will work as teams on specific projects. The role-holder will also collaborate with ECRs based
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include density functional theory (DFT) and higher level methods to accurately screen new systems based on their optoelectronic and vibrational properties. The role holder will develop and apply