This PhD project at University College London, within the Institute of Clinical Trials and Methodology (ICTM), focuses on developing innovative statistical design solutions for differential placebo effects in multi-arm multi-stage (MAMS) clinical trials with subjective outcomes. While MAMS trials are well established for objective outcomes such as cancer progression or survival, new challenges arise in neurodegenerative diseases like Parkinson’s, where primary outcomes are patient-reported and treatment regimens may differ (e.g., pills vs. injections). The project addresses the methodological challenge of ensuring fair and unbiased comparisons between active treatments and placebo when subjective outcomes are influenced by participants' perceptions of treatment regimens. For example, participants may believe that a more intensive regimen (e.g., three pills daily) is more effective than a simpler one, potentially biasing self-reported outcomes. This raises the question of whether separate placebo arms are needed for each regimen, which could undermine the efficiency of a single common control arm, or whether advanced statistical techniques such as Bayesian borrowing can be used to maintain integrity while minimizing the number of patients receiving placebo. Key objectives include evaluating different analysis strategies (such as averaging across placebo regimens, Bayesian borrowing, and adaptive merging of placebo arms), devising trial designs that control bias and type-1 error while maximizing statistical power, and writing a comprehensive statistical analysis plan for implementation. The project is directly linked to the EJS-ACT-PD study ( https://www.ejsactpd.com/ ), which is currently recruiting and provides a real-world context for methodological development. Applicants should have a strong quantitative background, ideally in statistics, mathematics, or a related field, and an interest in clinical trial methodology. Experience with statistical analysis, bioinformatics, or patient-reported outcomes is advantageous. The position offers the opportunity to contribute to cutting-edge research at the intersection of statistics, medical science, and clinical trial design, with potential impact on the conduct of trials in neurodegenerative diseases and beyond. Prospective candidates are encouraged to contact Professor James Carpenter (j.carpenter@ucl.ac.uk) before January 2, 2026, to discuss their interest and suitability for the project. The application deadline is November 26, 2025. For full application instructions and documentation, visit https://mrctmrpdtp.com/mrc-core-cti-opportunities/ .