392 data-"https:"-"https:"-"https:"-"https:"-"UNIV" Fellowship positions in United Kingdom
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evaluating predictive time series models and using R to manage, analyse and visualise data including developing re-usable code in collaborative projects using platforms such as Github is also essential
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evaluating predictive time series models and using R to manage, analyse and visualise data including developing re-usable code in collaborative projects using platforms such as Github is also essential
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of data collectors; and working with multi-country teams. Availability and willingness to travel abroad, including to Lebanon, are essential. Further particulars are included in the job description. The
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some but not all of the responsibilities outlined below. Analyse and interpret data Apply knowledge in a way which develops new intellectual understanding Disseminate research findings for publication
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, stakeholders, and the public to support the development and delivery of the research project. You will be involved in all aspects of the evaluation, including literature reviewing; data collection, analysis and
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of Manchester and Imperial College. This role involves computational modelling and experimental data analysis, integrating mathematical models of clock neurons and populations with in-vitro and in-vivo
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-emission vehicles, fleets, and associated infrastructure, including data analysis, impact assessment, and tool development. It will also involve interpreting and reporting total cost of ownership (TCO) and
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and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be
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About the role The work has a particular focus on quantitative analysis of the national data to estimate mental health needs which are both known and unknown to health services related to mental
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catalytic systems. The postholder will develop and apply advanced simulation techniques, analyse molecular simulation data, and contribute to collaborative research combining computational modelling with