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and resistance, and single cell RNA sequencing to characterise the resistant phenotype Apply mathematical frameworks to learn the dynamics of resistance evolution Combine experimental results with
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Software Development: Building the Next-Generation Trust Maturity Model Integrating DevOps practices into ML-driven systems: A Framework and Maturity Model for Continuous Machine Learning Development
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the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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of the workflow. While the majority of the project is computer based, there is a small lab-based component in order to generate cell samples to be able to acquire the NMR data. Once proof of concept has been
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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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an interdisciplinary approach to address this problem using dietary interventions on animal models of cognition. During this project you will learn techniques from a range of disciplines including: animal behavioural
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, biology, or a closely related discipline Desirable experience: optics and photonics, AI/machine learning, biology, or biomedical sciences Excellent English, analytical, and problem-solving skills UK
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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will also be able to access £2,500 of Proficio funding for professional skills development and conference attendance. Person specification You are passionate to learn more about sustainable fisheries
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avenues may include linking plankton size patterns to krill dynamics, carbon export or nutritional quality, or developing tools for rapid ecosystem monitoring using machine-learning approaches