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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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with these collaborators. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences
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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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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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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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support projects using GWAS, Mendelian Randomisation, and polygenic risk score analysis to uncover genetic mechanisms underlying complex traits. There are opportunities to integrate omics data across
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. By combining advanced AI recognition with live inventory monitoring, FabricFlow addresses long-standing inefficiencies in supply chains caused by manual processes, disconnected data, and lack
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by underrepresented groups Develop communication and education materials for local communities Apply/design appropriate analytical techniques to generate impactful insights. Formulate tailored
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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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. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences and skills of the successful