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, journalists and citizens in Germany, Italy, the UK and the USA. Surveys, interviews and focus groups are central to the data collection. The postdoctoral researcher will join the project team in its third year
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settings. More information on the project can be found here: https://cordis.europa.eu/project/id/101214413 The Post-Doctoral Researcher will support the co-creation of the TRANSCEND-XR intervention through
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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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position is intended for early stage researchers, either just after completion of a PhD or for someone entering a new area for the first time. If you have already completed your PD1 stage in UCD or will soon
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completion of a PhD or for someone entering a new area for the first time. If you have already completed your PD1 stage in UCD or will soon complete a PD1, or you are an external applicant whose total
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Recruitment Agencies. Any CV's submitted by Recruitment Agencies will be returned. The PD1 position is intended for early stage researchers, either just after completion of a PhD or for someone entering a new
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distinct cohort, in addition to refining how we collect and analyse these data. This project will involve working with existing large datasets, optimisation of data processing and statistical analysis
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completion of a PhD or for someone entering a new area for the first time. If you have already completed your PD1 stage in UCD or will soon complete a PD1, or you are an external applicant whose total
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highly valued: multispectral UAV mapping, coastal measurements (ADCP, Kestral, wind, wave, buoy), sediment analysis (particle size) and interpretation; CFD modelling; Irish coastlines and data science. The
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on this expertise. Inclusive Co-Learning and Inclusive Research with Students with Intellectual Disability in Higher Education The PATH 4 Phase 2 funded id+ futures Project delivers 2 rights-based, inclusive