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that seeks to achieve transformative and far-reaching impacts to address the contemporary polycrisis. Building on Dr Ian Hughes’ foundational leadership, and research with others across UCC and beyond, Deep
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Post-Doctoral Research Fellow to develop and apply advanced machine learning techniques to medical imaging and diagnostic applications, including Cardiac Magnetic Resonance (CMR), Echocardiography (ECHO
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an ideal candidate with expertise in cutting-edge fields like artificial intelligence (machine learning), deep learning, mathematical modelling and systems biology. Proficiency in clinical data analysis
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the advancement of explainable AI in the biomedical domain. The Post-Doctoral Researcher will be expected to perform research and development in the area of machine learning and deep learning applications
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imaging. DNNs have considerable potential to correct head motion in fMRI, as they can learn complex mappings, and exploit knowledge of brain structure. The PhD Candidates will develop DNNs to motion correct
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different strategies including homology-directed repair (Hollywood 2016; https://pubmed.ncbi.nlm.nih.gov/27557525; Santos 2021; https://pubmed.ncbi.nlm.nih.gov/34103250) and targeted excision of deep intronic
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at the cutting edge of micronutrient research. The ideal candidate will have/be: • A PhD qualification in Human Nutrition. • Deep knowledge of food data, including composition, intake and analysis. • Good
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-graduates, and early to mid-career professionals to lead the transformation that society needs in order to create a climate-resilient world, (iii) Deep Learning Demonstrations: Community-based learning
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of deep-time land ecosystem collapse Post Duration: 2 years Requirements Research FieldEnvironmental science » OtherEducation LevelMaster Degree or equivalent Skills/Qualifications Key duties and
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feature extraction by means of deep learning algorithms and the support to non-experts' decision for a personalised patient care. The project will also evaluate the clinical and economic impact in