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apply state of the art statistical methodologies, to enable personalised uncertainty estimates, for predictions made by clinical AI. Explainability – the postholder will apply standard approaches
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Attend UCL courses and training (e.g. in research study design, good clinical practice, medical statistics, time management, paper writing). Literature research Manuscript writing for submission to peer
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strong critical thinking and problem-solving skills, a high level of numeracy and the ability to interrogate large, complex datasets in Excel or statistical packages, you should have a background of
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behaving mice, and good proven programming skills with MATLAB or Python as well as good knowledge of statistics and complex neural data analysis. Excellent experience performing in vivo surgeries, such as
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programming skills in either MATLAB or Python, combined with knowledge of statistics and complex neural data analysis. Experience of working on hippocampal and/or medial entorhinal datasets and in in vivo
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accurate and up-to-date records. In addition, the applicants should have a high level of proficiency with computer software related to laboratory research, data presentation and statistical evaluation, as
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statistics) 8. Experience with clinical research and understanding of research methodology 9. Experience with data analysis 10. Good interpersonal skills to develop and maintain effective working
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, but not limited to, health informatics, digital health, bioinformatics, statistics, genetics, epidemiology, computer science, information systems engineering). Experience or knowledge of the role
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of stakeholders. They will have a keen eye for detail with an ability to identify patterns and trends and draw conclusions from these and they will be a highly experienced user of Excel and statistics
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documentation software, including git and Markdown. 6. Experience with statistical genetics approaches for functional genomics, including linkage disequilibrium score regression, cell type deconvolution and