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- UNIVERSITY COLLEGE DUBLIN (UCD)
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and cognitive trajectories with the aim of helping to lower the age of diagnoses. Machine learning techniques will be applied to combine datasets to establish the best predictive models for children’s
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at University College Cork. The department manages one of the largest private networks in Ireland, 2 datacentres, over 7000 computer workstations, 300+ websites, research infrastructure and a customer base of
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centres. Individuals for this role are expected to have proven experience applying artificial intelligence, machine learning, computational statistics, and statistics to specific problems, particularly in
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. Essential Qualifications Minimum PhD (or near completion) in Data Science, Health Informatics, Biomedical Engineering, or a related field. Expertise in predictive analytics and machine learning within
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broadly interpreted to include integration of Machine Learning, Implementation of Automation, Artificial Intelligence tools and AI-derived algorithms, Cheminformatics and utilisation of big data in research
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data science in industrial research settings (>6 years) or academic centres. Individuals for this role are expected to have proven experience applying artificial intelligence, machine learning
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programming, machine learning, and artificial intelligence domains. The Post-Doctoral Researcher will be expected to perform research and development in the area constraint programming, machine learning, and
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, computer science, or a related field is required, together with relevant expertise in areas related to Artificial Intelligence, such as: Foundational Models, Algorithmic Research Machine/Deep Learning Computer
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, Functional Genomics, Machine Learning or you can apply for the specific project titled “Machine learning applications in epigenomics.” The selected candidate will join a dynamic research group located
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artificial intelligence, machine learning, computational statistics, and statistics to solve specific problems. Relevant areas of interest include explainable AI, deep learning, graphical models, reinforcement