477 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions in Ireland
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Duration: 1 Year 9 Months, Part-Time Post Salary: €46,805 - €53,391 p.a. pro rata .8 FTE (IUA PD1 Salary Scale) For an information package including further details of the post see https://ore.ucc.ie
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-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/ Informal enquiries can be made in confidence
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submitted by Recruitment Agencies will be returned. Prior to application, further information (including application procedure) should be obtained from the Work at UCD website: https://www.ucd.ie/workatucd
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outstanding education are interlinked and equally valued. Professor Lorna Lopez and Professor Andrew Coogan invite applications for the position of research assistant on the “Ambient-BD” research project (https
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(which in addition to Geology also includes Geography, Botany and Zoology) and as part of the E3 learning foundry which includes the School of Natural Sciences, the School of Engineering and the School
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CERN. the CERN Collaboration and develop theory, simulations, and AI tools for application to data from the LHC and future colliders. https://doi.org/10.1051/epjconf/201919901022 - Central exclusive
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skills. Is passionate about talent development and committed to creating opportunities for learning and growth. Can lead reporting, maintain SOPs, and coordinate initiatives that strengthen governance and
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candidate will support the delivery of the 2-year MSc in Diagnostic Radiography and MSc Radiation Therapy programmes and teach and coordinate elements of the postgraduate MSc in Medical Imaging and Radiation
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the Work at UCD website: https://www.ucd.ie/workatucd/jobs/ Where to apply Website https://www.aplitrak.com/?adid=TGluZGFtZWlsaS4yNDA5MS45OTA4QHVuaWNkdWJsaW4uYXBs… Requirements Skills/Qualifications
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) approaches. Design predictive maintenance algorithms using machine learning, statistical learning, and digital twin-based models to anticipate failures and optimise maintenance interventions. Integrate AI