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Field
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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to forward a copy of your CV along with your academic referees. Informal enquiries to:Colin.clarke@nibrt.ie or niall.barron@nibrt.ie Funding:Annual stipend of €25,000 plus fees for 4 years.Project 2: Model
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain
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seismic data to produce 3D geophysical models that will constrain the subsurface extent of rock units that might be suitable for hydrogen generation via radiolysis and/or serpentinization and identify
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have
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applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be inherently dangerous demanding very precise assembly tasks, and so flexible automation
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scientific literature and interviewing stakeholders; and conduct a cross-region survey on implementation conditions for One Health. Throughout the project, feedback from stakeholders like poultry farmers
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of limited value. An eHTA requires building a health-economic model and scenario analyses, which will help determine the plausible range of health improvements and cost consequences. As more data become