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programming languages such as C#, Python, and C++. Experience with data analysis techniques and AI methods. For informal queries please contact: Dr. Patricia Cornelio - patricia.cornelio@bristol.ac.uk To find
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housing development. Perform parametric building performance modelling. Conduct non-intrusive load detection data analysis and reporting. Conduct financial modelling (carbon analysis, cost-benefit
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design, statistical analysis, and results reporting. The role will also involve planning and managing project activities, building research skills and networks, and engaging with academic and industrial
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systematic reviews and become familiar with statistical analysis. They will also contribute to undergraduate and postgraduate teaching. This is a full-time post (40 hours per week), and you will be offered
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analysis programs, and excellent communication, interpersonal, and problem-solving skills are also essential for this role. Appointment as Research Fellow is dependent upon having been awarded a PhD; if this
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for those who teach and/or support learning across the tertiary sector to provide a sector analysis of current practice including similarities and differences in needs and approaches. 2. Identify the current
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simulation and data-driven analysis, managing research activities, and contributing to both academic and non-academic outputs. You will represent the project in technical discussions and international meetings
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community, all while developing your research skills and fostering collaborative partnerships. Your responsibilities will include: Conduct Research and Analysis: Undertake research design, data analysis, and
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and experience in extracting useful knowledge from remote sensing data. About the Role To carry out research involving the integration of drone-based imaging, multispectral data analysis, phenotyping
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, management, and qualitative analysis of data sources related to forced labour risk and decent work assessment of the food system. The purpose of this role will be to support the principal investigator