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they become apparent. Leading on code modernisation activities with reliability, robustness, performance, and portability in mind to meet the needs of the user community. Leading on code review meetings and
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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 equality and diversity, data protection, copyright and licensing, security, financial and other University policies, procedures and codes as appropriate. Take reasonable care for the health and safety
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Strategy and a central part of everything we do. We also live by our values and our Staff Code of Conduct. At Durham we actively work towards providing an environment where our staff and students can study
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-quality code, and will contribute to the sustainability and usability of open-source tools developed within the project. Main Duties The responsibilities may include some but not all of the following
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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 funds Set up and maintain project codes, student codes, workpackages, and purchase orders for Training Grant consortia Compliance & Data Management Provide guidance on funder financial rules and budgetary
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and Experience Strong statistical analysis and data handling skills Understanding of data structures, data modelling and data management Ability to write robust, reproducible code in Python or R
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statement from your supervisor committing to support your finalization phase Compliance with the CoBeNe regulations for PhD candidates (agreement to the Code of Good Practice, FÖP within the first 2 semester
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8090F select ‘‘PhD Mechanical Engineering (full time) - 8090' as the programme of study You will then