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Analyse specific requirements and architectures to design appropriate objects and methods for implementing functional and non-functional requirements. Proactively manage complex risks, issues, and
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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technologies will affect them. It is our anticipation that the work will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly
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understanding of gene presence/absence, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid
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: Effective interpersonal and communication skills relevant to teaching and consultancy environments. This includes effective presentation and facilitation skills, and in the use of flexible teaching methods
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lesion tissue identified by exome or gene panel sequencing. This will involve optimisation of droplet digital PCR (ddPCR) assays or Sanger sequencing for independent validation depending on the estimated
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degraded ecosystems across different habitat types. This is important for establishing the extent to which ecoacoustic methods and metrics are transferrable between places. There is scope within this project
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People with disabilities are excluded from the assistive technology creation process because the methods and tools that are used are inaccessible. This leads to missed opportunities to create more
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(e.g., C++, Unity, Python) a background or interest in human-computer interaction, gender studies, and/or construction familiarity with qualitative and quantitative research methods. How to apply We
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methods dealing with model complexity - e.g., AIC, BIC, MDL, MML - can enhance deep learning. References: D. L. Dowe (2008a), "Foreword re C. S. Wallace ", Computer Journal , Vol. 51, No. 5 (Sept. 2008