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Field
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This PhD project focuses on developing formal methods and knowledge representation techniques for the modelling and analysis of complex manufacturing and intralogistics systems, such as highly automated
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techniques and data analysis and interpretation. Proven ability to work independently, think critically and creatively, and solve complex problems. Experience publishing in high-impact journals and presenting
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microscopy, image analysis: Development of microscopes, fluidics, and data analysis pipelines used to acquire and quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering
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scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT
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been steadfastly committed to serving society by advancing analysis- and evidence-informed policy. Guided by this exacting mission, our community of faculty, students, and alumni from the public, private
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project establishes a scalable framework for automated atomic-scale image analysis that can be extended to more complex defect types, materials, and computational microscopy applications. Fellowship 2
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research data; this may be through a variety of research methods, such as ethnography and non-participant observations, and research interviews Analyse and interpret data using qualitative analysis methods
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for the position. Preferred selection criteria Experience with shotgun sequencing metagenomic analysis and microbiome profiling of complex environmental samples Experience with statistical modelling and multivariate
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treatment optimisation. Tooth preparation, white spot lesion models and imaging will also be main important supporting elements, including quantitative analysis and integration with the wider team working
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for the production of complex porous structures B.CAD modelling and CFD simulation of TPMS structures and other geometries applicable to chromatography. C.Production and physical, morphological and