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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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wide variety of backgrounds learn from one another, share ideas, and work collaboratively. UCC is committed to being an employer that recognises the value of diversity amongst its staff. We encourage
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of Pharmacy, UCC, led by the Professor of Pharmaceutics, Brendan Griffin is aiming to develop Artificial Intelligence (AI) and machine learning tools that can accelerate the creation of medicines for conditions
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wide variety of backgrounds learn from one another, share ideas, and work collaboratively. UCC is committed to being an employer that recognises the value of diversity amongst its staff. We encourage
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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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people from a wide variety of backgrounds learn from one another, share ideas, and work collaboratively. UCC is committed to being an employer that recognises the value of diversity amongst its staff. We
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their experience and qualifications meet the criteria. Desirable Practical experience in developing AI/machine learning solutions Experience with Open Radio Access Networks (Open RAN) Strong knowledge of AI and
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; Green Campus Initiative ’ Competitively priced café and restaurant Equality, Diversity & Inclusion forums, and network groups Employee assistance programme with Spectrum Life Learning and Development
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population where people from a wide variety of backgrounds learn from one another, share ideas, and work collaboratively. UCC is committed to being an employer that recognises the value of diversity amongst
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feedback to students, generating insights to inform practice, improving learning outcomes and reducing division between students who can afford outside help and those who can’t. The project is funded through