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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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questions for research interviews. Conducting a series of semi-structured interviews at UoN. Transcription and analysis of qualitative data. Attending research team meetings. Contributing to publication
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to perform complex synthetic tasks. You will be trained in synthetic organic, polymer, and supramolecular chemistry. For more information on the group visit: www.deboresearchgroup.com [deboresearchgroup.com
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-3413 ), 4-Limited flight data for adaptive methods (doi.org/10.1016/j.geits.2022.100028 ), and 5- Failure to use a robust state estimator to increase robustness of EMS in eVTOL, have not been filled by
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nature of this project, please contact Prof. Tony McNally (T.McNally@warwick.ac.uk ) directly for further information. Essential and Desirable Criteria: 1 or 2.1 degree in chemistry, chemical engineering
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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of marginalised communities through documents, interviews, and focus groups to understand their views on health data governance. Additionally, you will also be responsible for managing some organisational elements
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disciplines and sectors. More information can be found at www.ukri.org and www.mrc-lmb.cam.ac.uk. Closing date: 07/09/2025 Final appointments will be subject to a pre-employment screening. We actively support
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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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ADTKD diagnostics and clinical trials. What you’ll do You will work at the interface of laboratory and data science, and clinical genetics. You will: Establish and characterise the UK ADTKD-MUC1 cohort