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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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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 8 hours ago
of questionnaires and interviews. Assist with grant writing, including drafting proposals, identifying funding opportunities, and supporting the submission process. Lead or contribute to systematic reviews and meta
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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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skills and experience: Essential criteria Upper second or first degree (BA, BSc or equivalent) and PhD in behavioural, social, management or health sciences, or in a discipline with a health-related
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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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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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an industry partner you will conduct a series of investigative processes (e.g. systematic reviews, meta-analyses, observational and intervention studies), to evaluate the efficacy and current usage of different
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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
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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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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta