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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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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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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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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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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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scholars in Law and two PhD students (one in Law and one in Computer Science/Data Analytics), as well as with international, European and national stakeholders involved in the CURE project. The post-holder
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using public and proprietary data as well as sensitivity analysis of analytical modelling results against known outcomes. The developed models will then be applied to examine the impacts of various
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application of analytical pipelines to data generated by the WaSPP network. What you would be doing This is a three-year post that would suit a biologist or mathematician (or similar) with research experience
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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
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workflows of bioimaging analysis to quantify advanced imaging data generated by super-resolution STED microscopy, FLIM, FRET and FCS. Candidates must hold a PhD in cell biology, biophysics or biochemistry