208 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" positions in United Kingdom
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, open code, open educational resources and practices that support replication. Desirable: F1 Experience of object-led research and teaching. F2 Experience of, or demonstrated potential for, research
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experience of research project supervision. E5 Commitment to open research, as appropriate to the discipline, through open data, open code, open educational resources and practices that support replication
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/ProvinceNorfolkCityNorwichPostal CodeNR4 7UQStreetColneyGeofield Contact State/Province Norfolk City Norwich Website https://quadram.ac.uk Street Norwich Research Park Postal Code NR4 7UQ E-Mail nbi.recruitment@nbi.ac.uk STATUS
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for adaptation planning. The project is fully desk-based and supported by existing climate datasets. You will gain advanced training in climate data handling, statistical downscaling, GIS, and reproducible coding
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Commitment to open research, as appropriate to the discipline, through open data, open code, open educational resources and practices that support replication. Experience Essential E1 Experience of making
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analysis, as directed, assist with coding, compile a bibliography, and support production of a report. Candidates should hold an SCQF Level 10 qualification (Honours degree) in a social science discipline
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data collation and analysis, as directed, assist with coding, compile a bibliography, and support production of a report. Main Duties and Responsibilities Perform the following activities in conjunction
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Commitment to open research, as appropriate to the discipline, through open data, open code, open educational resources and practices that support replication. Experience Essential E1 Experience of making
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appropriate to the career stage, including some experience of research project supervision. E5 Commitment to open research, as appropriate to the discipline, through open data, open code, open educational
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship