487 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" positions in Ireland
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to application, further information (including application procedure) should be obtained from the Work at UCD website: https://www.ucd.ie/workatucd/jobs/ Where to apply Website https://www.aplitrak.com/?adid
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–machine collaboration will ensure that factories remain productive, sustainable, and resilient even in the face of volatility. FLARE addresses significant challenges related to process design, system
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Months, Full-Time Post Salary: Post-Doctoral Researcher Salary: €46,306 - €52,863 p.a. (IUA PD1 Salary Scale) For an information package including further details of the post see https://ore.ucc.ie
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cancer trials units at Cork University Hospital (Cancer Trials Cork @CUH), University Hospital Waterford and Bons Secours Hospital Cork). For more information about the group, check our website: https
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Living Lab, co-creating learning experiences, training programmes and public engagement activities with stakeholders including residents, schools, industry partners and civic organisations. WATERWAY also
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. PhD Project Description Project Title: Photonic-Inspired Federated Learning for Communication-Efficient Next Generation Radio Access Networks (NG-RANs) Description: This PhD project will develop a novel
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/or taste and sensory science:(http://www.maynoothuniversity.ie/study-maynooth/undergraduate-studies/courses/bsc-food-science-and-human-nutrition ). Candidates should have prior experience delivering
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qualifications / experience and in line with Public Sector Pay Policy (€43,425 - €103,582 per annum) https://www.tcd.ie/hr/assets/pdf/monthly-academic.pdf Hours of Work: Hours of work for academic staff are those
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the manufacturing challenges associated with producing rAAV and brings together experts from two leading Irish institutions, NIBRT and UCD, and APC-VLE Ltd. (https://approcess.com/services/cell-and-gene-therapies
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will support two projects, one of which is “SMART-FLOW: Harnessing Multimodal Data and Machine Learning to Optimize Fluid Management in Intensive Care” and is funded by the Spark Innovation Programme of