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of protective immunity. This project will provide new insights into mechanisms of immunity deployed against this notorious human pathogen. Emerging evidence suggests that a critical bottleneck that has faced
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will contribute to our ability to understand and predict this critical component of ecosystem function. You will work within group spanning ecological science, engineering, and computer science methods
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critical component analysis, and (iii) development of Automation of ML model and data selection. The applicants should have knowledge of machine learning and optical networks and willing to engage in testbed
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foster resilience among international protection beneficiaries. The methodology combines desk-based analysis across legal and ethical disciplines, with semi-structured interviews with lawmakers and
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this project, using extensive primary cell culture, molecular analysis, scRNAseq, non-invasive imaging analysis, along with mechanistic studies using 2D/3D culture models, we will dissect the distinct cellular
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-centered and psychologically informed methods that could encourage responsible behaviours. Designing such approaches for opaque generative models, such as Large Language Models (LLMs), is critical and is
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for structural variants and copy number variants (SVs/CNVs), will be used to optimize data analysis and variant discovery. The project will focus on identifying previously overlooked pathogenic variants, exploring
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. Initial research has shown that the placement of network functions, along with their scaling up and down, plays a critical role in overall energy efficiency. However, there is a significant gap in real
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understood, and the identification of targets of early intervention presents a great challenge. To address this critical knowledge gap, PREVENT, a large-scale population study carried out by Trinity College
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) Computational Fluid Dynamics (CFD) Modelling [may involve groundwater modelling with heat transfer depending on the chosen candidate] 3) Energy calculations and life cycle assessments (LCA analysis) 4) Conducting