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fieldwork, data processing, project reporting and administration as deemed appropriate by the PI. The Successful candidate will support the DETECT project which aims to assess coastal vulnerability and model
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digital assets. The successful individual will bring a strong track record of strategic senior leadership experience in a large and complex organisation and ideally in the higher education sector. They will
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) out to 2050. Tasks include compiling big-data inputs, developing CNOSSOS-EU compliant simulations, validating predictions with field/lab measurements and mapping future hot-spots. Ideal profile: honours
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interdisciplinary study that will assess the pre-/and post-radon concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model
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concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model (CONTAM), which will be parameterised based on representative
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the Trinity Centre for Ageing and Intellectual Disability, Trinity College Dublin. IDS-TILDA is a large scale nationally representative study of people with an intellectual disability aged 40 years and over
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, driven by future applications and services for 6G and beyond. Networks are also evolving to support a large variety of signals across larger access and metro network areas. For these novel scenarios
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available Large Language Models to parse, extract and interpret the most useful peer-reviewed scientific information of inflammatory bowel disease within public repositories. Experience with previous
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work closely with the PI on the analysis of grey literature reports, managing and proofing large datasets and compiling data. Applicants will preferably have a Postgraduate degree in Zooarchaeology and
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7 Months, Fixed-Term, Whole-Time Post Position Summary As evidenced by a growing body of literature, the gut microbiome plays an important role in inflammatory bowel diseases. However, the large