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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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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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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
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Responsibilities of the Post Conduct research and development on sign language recognition using computer vision and machine learning techniques. Lead the implementation of inference models suitable for mobile and
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the PI with a team of PhD students to establish and optimise robust synthetic methodologies based on DES systems; carry out in-depth structural, photophysical, and electrochemical characterisation
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in electrochemistry and battery research. The candidate will have a PhD in Physics, Chemistry, Materials Science or a related discipline, or equivalent experience, with significant postdoctoral
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. The successful candidate will be expected to follow a curriculum of learning to achieve a rounded education in all aspects of rare bone conditions with the option to complete a designated research project. To
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University we strive to create a workplace that reflects the diversity of our student population where people from a wide variety of backgrounds learn from one another, share ideas, and work collaboratively