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prioritise work independently while contributing effectively to a collaborative project team. You will understand the importance of research ethics, safeguarding and data protection in applied fieldwork
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with expertise in areas such as Machine Learning and Deep Learning, Generative AI, Data-Centric and Responsible AI, or AI for real-world applications (e.g., health, cybersecurity, robotics, or business
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research on this topic. Projects have been designed to generate tangible outputs such as published papers, software or data sets within a 12-month period. The fellowship should not be viewed as an
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will also work alongside other team members to examine patients’ responses by analysing EEG and behavioural data. Candidates are expected to hold a medical qualification (MBBS or equivalent) and be fully
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-quality, repeatable data. Develop and apply signal processing workflows for weak transient signals, long-term monitoring, feature extraction and statistical analysis. Support sound playback/stimulation
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or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be found on our Equality and Diversity Intranet page .
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orientation, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be found on our Equality and Diversity Intranet
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and champion the Student and Staff Active programmes, coordinating resources and supporting student volunteers. ● Insight & Evaluation: Design and analyse surveys and participation data
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information sharing in domestic abuse cases, with a particular emphasis on Clare’s Law/ the Domestic Violence Disclosure Scheme. The aims of the project are to understand how, when, in what circumstances, and
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tradeable points can be used under the rules. Information on other visa options is available at www.gov.uk/check-uk-visa . Please do not hesitate to contact Grant Rae, HR Adviser (e-mail: grant.rae@abdn.ac.uk