25 algorithm-development-"Multiple"-"Prof"-"Prof"-"SUNY"-"St" research jobs at MAYNOOTH UNIVERSITY in Ireland
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models to more complex dynamical land surface models. A core output from the overall project will be the development of novel and automated methodological approaches to characterise urban building stock
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output from the overall project will be the development of novel and automated methodological approaches to characterise urban building stock based on available, existing imagery which will be developed in
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to the development of a state-of-the-art population-based analytic data system that serves multiple needs of decision support, population monitoring, and comparative effectiveness research The position is based
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providers, industry stakeholders and student partners. The project entails developing a new curriculum aimed at providing learners with enhanced technical and work readiness skills of relevance to the modern
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on developing and implementing a knowledge and evaluation framework. They will assist with managing all stages of the work package including the measurement of impact on employability and career prospects
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with extending and delivering the TROPIC training programme for open research, and to help develop and coordinate a national network of open researchers in Ireland. The work is being led by Dr. Dermot
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both education technology providers, industry stakeholders and student partners. The project entails developing a new curriculum aimed at providing learners with enhanced technical and work readiness
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Rescue – enhancing the joint WMO–C3S data rescue portal, developing a prototype image repository, improving the Data Deposition Service, and developing innovative approaches to data rescue, including
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. This work covers three main areas: Data Rescue – enhancing the joint WMO–C3S data rescue portal, developing a prototype image repository, improving the Data Deposition Service, and developing innovative
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portal, developing a prototype image repository, improving the Data Deposition Service, and developing innovative approaches to data rescue, including student involvement, AI/ML and international