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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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, 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
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the Blackholistic collaboration, which is funded by an ERC Synergy grant and aims to try and unify accretion and jet formation across the black hole mass range. The collaboration incorporates observations, analytic
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biophysics, and cutting-edge analytical technologies. Your expertise in optical microscopy, single molecule imaging, computational imaging and data analysis will help us further develop mass photometry and
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on qualifications and relevant skills acquired and will also be determined by the funding available. About you You will hold a PhD/DPhil or be near completion of a PhD/DPhil in a related subject area and have
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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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executing research programmes related to different aspects of thymus biology employing informative experimental models and a broad range of analytical platforms, including single cell transcriptomic analysis
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completion of a PhD in Psychology or a relevant area along with experience of collecting data from research participants. With excellent data analytic skills, you will be familiar with SPSS and at least one
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existing machine learning methods, as well as building robust, well-documented, and reproducible analytics pipelines for long-term use by the wider team. You will carry out data analysis and manage
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of mixed phase numerical or analytical flow modelling for icing. Experience conducting and analysing experimental data is desirable. You should have a record of academic publications in the field and be able