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Collaborate with CCY researchers on ongoing projects and contribute to the development of new research initiatives Contribute to data analysis and data management Contribute to national and internationals
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performance, detect artefacts, and ensure scientific rigor Proficiency in Python (or Julia/R) for data handling, ML model development, and statistical analysis Ready to work with time‑series data, sensor fusion
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familiarity. Previous research experience (thesis, publication, or research assistantship) in psychology, cultural studies, or computational analysis. Capacity to work independently while contributing to a
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) within the scope of the project “FMC Fire - Determination of Exposure Risk and Management of Civil Protection Assets in Forest Fires through Remote Analysis of the Moisture Content of Forest Fuels”, with
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/Qualifications - Automation or applied mathematics background, with a strong interest in physical models and numerical method - Analysis of partial differential equations, variational approach, Bayesian estimation
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chemistry modelling techniques scientific machine learning high-performance computing molecular design, generative AI, database handling and analysis collaborative, project management, presentation and
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monitoring methods with community partners across Scotland’s west coast. The potential for drone and mobile phone imagery to enhance this work has been discussed with community groups, informing this project
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for donor kidneys. Central to this is the use of machine learning to evaluate the predictive value of biomarkers from various sources: donor-related data, perfusion fluid, and kidney biopsies. Kidney biopsies
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vocabulary development. The position is part of a project funded by the Leverhulme Foundation testing a neural process theory of vocabulary development. The successful candidate will work with Prof. Larissa
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integrated into the analysis of integrated assessment models (IAMs), which are used to support policymakers in designing effective climate strategies. In this PhD project, you will work on improving