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The SSHRC-funded HubMeta Lab project is undertaking the largest-ever meta-analysis of SME growth studies (over 2,500 full-text articles coded to date). We have uncovered extraordinary variability in
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of architected interfaces. The PDRA holding this position will work closely with members of MEGA Slab and will assist with supervision of MSc and PhD students. The PDRA will contribute to the project
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researcher interested in studying human-associated microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational biology
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postdoctoral researcher interested in studying human-associated microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational
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have: a PhD or equivalent qualification (or be nearing completion thereof) in Materials Science/Engineering or another subject relevant to the study, development and/or application of nanostructured
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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duration of 2 years with a possibility to extend up to 5 years upon the performance and funding availability. The successful candidate is expected to theoretical and experimental research on meta-MAC layer
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oversee quantitative and/or qualitative data analyses, literature reviews, systematic reviews, and meta-analyses Prepare, write, and review research manuscripts, reports, and presentations for internal
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on soil organic matter cycling Literature research and (meta-)analysis to provide evidence-based knowledge for model parameterization Quantify the coupled carbon and energy turnover of specific biomolecules
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on machine learning, and developing and applying simulation methods and models for equilibrium and nonequilibrium molecular dynamics simulations. You will model meta-lactamases enzymes involved in resistance