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affect these trajectories using discontinuous growth modelling and/or other appropriate statistical analyses. Additionally, the student will conduct a qualitative interview study to understand
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participants, administering standardised cognitive and clinical scales, accompanying participants for brain scans and associated tests and maintaining study databases and assisting with statistical analysis
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legibility will be evaluated against human response times of user confirmations in a variety of scenarios, using appropriate statistical testing to test the efficacy of the models. The project forms part of a
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control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong foundation in mathematical and control theory is
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within CONNECT. The researcher will also be part of the School of Computer Science and Statistics in TCD. The position will be under the direction of Prof. Marco Ruffini and Prof. Dan Kilper Please see
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Award summary 100% fees covered, and a minimum tax-free annual living allowance of £19,237 (2024/25 UKRI rate). Overview The School of Mathematics, Statistics and Physics invites applications for a
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generalisability compared to traditional adaptive control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong
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validating joint models for clinical prediction. Applicants should have: Obtained or working towards a 1st class degree in Mathematics (BSc/MMath) or Distinction level Masters in (Bio)Statistics, Data Science
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subject, such as psychology, biology, human genetics ii) an MSc in a relevant subject involving human genetic research or child development research iii) Prior experience working with statistical packages
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data-driven approach, involving data science/statistics/machine learning methods, and will be informed by clinical literature and practice. NOTE: Applicants must have been resident in an EU member state