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in Medicine, contributing to the study design and analysis of data alongside the development and application of new analytical methods independently or in collaboration with others. This post will be a
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analytical techniques, opportunities to supervise students, and involvement in manuscript preparation and future grant applications. It is essential that you hold (or are close to completion) a PhD in cell
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potential spinout. You will hold a relevant PhD/Dphil (e.g. Chemical Engineering, Chemistry, Materials Science, etc.) or be near completion* together with relevant experience and possess significant knowledge
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our multidisciplinary team working at the interface of epidemiology, data science, and public health policy. The successful candidate will develop and apply advanced mathematical and computational
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others, pseudospectra theory, and empirical data from DRAGNet and global demographic databases (COMPADRE, COMADRE, PADRINO). The project combines mathematical modelling, simulation, and empirical synthesis
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Fritzsche, conducting individual research, analysing detailed and complex qualitative and/or quantitative data from a variety of sources, and generating original ideas by building on existing concepts. You
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access, analytical methods, and protocols, maintain clear documentation, and coordinate data exchange with partner sites and repositories. They will contribute to project design, manuscripts, presentations
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should possess or be close to obtaining a PhD in physics, materials science, or physical chemistry. They should be highly experienced in high-resolution, analytical scanning transmission electron
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analytical and/or computational approaches to many-body quantum systems, differential equations, and quantum computing. This includes carrying out collaborative projects with colleagues in partner institutions
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, data analysis, and modelling, in collaboration with the University of Southampton and the National Physical Laboratory (NPL). With a background in Materials Science, Physics, Chemistry, or Engineering