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Field
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possess a relevant PhD in Turbomachinery (or Chemistry and) Computational Fluid Dynamics, a strong multi-physics modelling background in Machine learning, a strong record of publications, proven competence
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between the two linked studies as well as taking the lead in the large-scale qualitative secondary analysis of interview data from multiple sources. In this role you will be expected to contribute
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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You will have or be close to the completion of a PhD/DPhil in epidemiology, biostatistics or big data, along with demonstrable experience of working with population registers and large datasets. With
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, and computational humanities. The postholder will lead the curated stream of the project, which involves designing a large corpus of Latin texts, curating it (correction of pre-processed data and corpus
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spatially offset Raman spectroscopy (SORS) as a healthcare tool for use in the community for bone health. We are seeking a data analyst with a PhD in data science and expertise in chemometrics, machine
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relevant to setting a roadmap for ongoing experiments, as well as recently developed applications of tensor network techniques to large-scale partial differential equations. We are advertising two positions
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they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI
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be close to the completion of a PhD/DPhil in epidemiology, biostatistics or big data, along with demonstrable experience of working with population registers and large datasets. With proven
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skills (e.g. Python, Julia) to merge concepts of chemical engineering, operations research and computer science, as you may also need to deploy machine learning to support data analytics and complex