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in minutes, and published on https://apply.uc.pt/ . VII.IX - Jury Composition: President: Maria Goreti Ferreira Sales Effective Members: Ana Rita Aires Cardoso, Liliana Patrícia Teixeira Carneiro
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
Selection Criteria: PD&PEWER_Academic B_Research Fellow.pdf About the opportunity This position is a fixed term for a period of up to 12 months to play a major role in building a model of hydrogen
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data engineering, statistical modelling and natural language processing, including from partners at the South London and Maudsley NHS Foundation Trust and King’s College London. You will be supported
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, namely: needs diagnosis and assessment; development of artificial intelligence-based forecasting models; and development of optimal control models. Relevant experience directly in the project’s area – 5
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to analyze large multi-modal datasets and/or who wish to deploy the next generation of exposome AI models. These positions come with data ready to analyze: the candidate can focus on developing research
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evidence that informs healthcare investment, service design and innovation, with a focus on understanding the cost of delivering healthcare, evaluating new models of care and improving health equity. This is
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repair on RNA-DNA hybrids of R-loops using computational modeling and molecular dynamics simulation along with various types of AI tools and machine learning approaches. Temporary Expertise in
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advantageous. Possess understanding of healthcare innovation concepts (e.g., service design, business model development, commercialisation, care automation, health economics and value capture). Strong analytical
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Responsibilities Architect and implement large-scale, georeferenced 3D digital twin models Develop computational pipelines for integrating vector, raster, terrain, LiDAR, and photogrammetric data Design procedural
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learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the