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experimental observations of fatigue and corrosion fatigue failure in AM samples. The goal is to establish causal pathways for understanding failure in AM components. The position will involve development
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scenarios under aggressive conditions) on the porosity and microstructural evolution in additively manufactured metallic samples, by the development of advanced computational multiphysics models of stress
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to characterize individual tumour cells isolated from patient blood samples. The project builds on molecularly imprinted polymer (MIP)-based probes developed by MIPrecise partners to selectively capture and
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sample preparation Desirable Qualifications Prior experience with negative ion mode MS is an advantage Interest in computational proteomics workflows Programming or scripting skills (e.g., Python, R
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involved in: Analysis of data from medium and low-cost sensors Analysis of data from cognitive performance assessments and health survey responses Conduction citizen science-based activities in the schools
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students. In the project you will: Perform longitudinal proteomic and degradomic analyses of wound healing models and clinical samples. Identify proteolytic cleavage sites and post-translational
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around public transport stations, travel survey data, and satisfaction survey data. Further data is expected to be collected during the project. The focus will be on analysing and modelling the factors
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directly identify and characterize bacterial pathogens, such as Listeria monocytogenes , from enrichment samples without the need for further culturing within one day. The new food safety tool will leverage
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international research experience. Responsibilities and qualifications You will develop sampling and characterization methods to analyze the composition of current footwear. This includes applying advanced
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sampling and characterization methods to analyze the composition of current footwear. This includes applying advanced analytical techniques to assess materials in both pre- and post-consumer shoes