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Research Fellow in AI for Healthcare (1 FTE) – ArcHub ICUSafeNotes-School of Computer Science 011287
breakthroughs into commercial healthcare solutions. In the ICUSafeNotes project, we are conducting research and development of multimodal machine learning models that includes ICU note summarisation and analysis
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experience Evidence of experience with public-patient involvement and stakeholder engagement Track record in scientific publication and dissemination Experience with Machine Learning Algorithms and Artificial
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): Research experience with literature review, data collection from different stakeholder groups. Advanced skills in using Stata or R. Machine Learning experience Artificial Intelligence Excellent written, oral
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to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join us at RCSI, where your contributions will be recognised, and you will be
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at Trinity College Dublin (TCD) seeks to appoint an outstanding, enthusiastic, and highly motivated Research Fellow who will contribute to a project that uses machine-learning methods to forecast
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every colleague is valued and empowered to thrive. Our dedication to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join
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colleague is valued and empowered to thrive. Our dedication to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join us at
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will also contribute to the CAPACITY project, applying tools such as the TIMES-Ireland Model to support robust decision-making on Ireland’s decarbonisation pathways. Applicants must hold a PhD in
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Experience The successful candidate should be able to demonstrate the following: Essential A PhD in education or a related field (sociology, social policy, psychology, economics); Strong quantitative research
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Undertaking (IHI JU), SEARCH boasts an initial budget of over €15.2 million. SEARCH aims to develop high-quality synthetic datasets that simulate real healthcare data for research, AI, and machine learning