3-year PhD position: Improving the measurement of EDI-relevant treatment effect modifiers in clinical trials
Randomized controlled trials (RCTs) underpin regulatory and clinical decision-making in healthcare, yet they are primarily designed to estimate average treatment effects within selected samples. This raises concerns about external validity and equity, as underserved groups are often underrepresented due to restrictive eligibility criteria and structural barriers to participation. Even when included, patient characteristics that are relevant to considerations of equity, diversity and inclusion (EDI), including demographic, psychosocial, contextual characteristics, are captured inconsistently across RCTs and sometimes with insufficient detail to determine whether findings apply across population groups. Recent guidance, including the 2024 revision of the Declaration of Helsinki and World Health Organization recommendations, calls for improved reporting of EDI-relevant patient characteristics. Frameworks such as PROGRESS-Plus identify key domains but provide limited direction on how these constructs should be measured in practice.
In addition to demographic factors, psychosocial and contextual characteristics such as health literacy, treatment preferences, financial constraints, and social support shape patients’ engagement with treatment but are rarely measured systematically in RCTs. As a result, little is known about whether underserved populations respond differently to treatments and which psychosocial or contextual factors may explain differences in treatment engagement and outcomes, particularly in chronic physical and mental health conditions that require sustained engagement and self-management.
This PhD project will examine how EDI-relevant characteristics are currently measured in late-phase clinical trials, identify and appraise candidate instruments, and evaluate selected measures within a large e-cohort of patients with chronic conditions. Embedded within the Horizon Europe EDICT Doctoral Network, the project aims to generate methodological and empirical insights to inform more consistent and equity-relevant measurement in future clinical research.
Overarching research question
How are EDI-relevant patient characteristics currently measured in clinical trials, and how can these measurements be strengthened to support the study of treatment effect moderators and treatment engagement in underserved populations?
Specific objectives
- To characterize how late-phase clinical trials in chronic physical and/or mental health conditions measure EDI-relevant patient characteristics, including how these constructs are defined, operationalised, and used analytically.
- To identify and critically appraise available instruments for measuring priority characteristics.
- To describe the distribution of key EDI-relevant characteristics across underserved patient groups within a large e-cohort, and to explore their associations with treatment engagement and patient-reported outcomes.
The doctoral candidate will aim to publish the findings of these studies in peer-reviewed international journals and integrate them into a doctoral thesis.
Candidates will be expected to participate in structured doctoral and network-wide training within the EDICT programme (minimum 25 ECTS at the host institution plus 10 ECTS network modules), including training in EDI in clinical trials, stakeholder engagement, research translation, research integrity, grant writing, and leadership.
Candidates will complete two secondment placements (typically 3 months each) in leading research institutions and/or non‑academic partners (e.g., industry, clinical trial networks, patient engagement or policy organisations).
Profile required :
We are looking for a candidate who meets the following essential criteria:
- A Master’s degree (or equivalent) in public health, epidemiology, biostatistics, psychology, or a closely related discipline that allows enrolment in a doctoral programme.
- A strong academic record and solid training in quantitative research methods.
- A very good command of written and spoken English.
The following qualifications would be considered an asset:
- Experience with systematic reviews, and/or clinical trial methodology
- Initial training in, or a clear interest in, measurement science, including clinimetrics or psychometrics.
- Strong interest in equity, diversity and inclusion (EDI) in clinical research.
- Experience using statistical software such as R, Stata, or similar tools.
Compliance with the MSCA mobility rule: candidates must not have lived or worked in France for more than 12 months in the 36 months prior to recruitment (excluding holidays and compulsory national service).
Supervision
The doctoral candidate will be supervised by Prof. Viet-Thi Tran and Dr. Karolin Krause at CRESS – METHODS, with regular meetings and close guidance on study design, analysis, and publication.
The candidate will be integrated into an intellectually vibrant and international unit in clinical epidemiology, with opportunities to present their work in team seminars and receive feedback from senior and junior researchers.
Team : CRESS U1153 – Team METHODS
Location : Paris, France
Starting date: September 2026
Duration of employment: 36 months
Condition of employment :
- PhD – MSCA Doctoral Network (36 months)
- Full time under MSCA rules (paid leave, social benefits, mobility/family allowances).
Salary : Gross salary of €4,735, plus a mobility allowance of €710 per month (gross). Estimated net salary after French social security contributions is approximately €3,038 per month (before income tax). This is complemented by partial reimbursement of transportation costs and, where applicable, a family allowance of €660 per month (gross).
Deadline : 30 March 2026
Team contact and application details:
Additional information on this PhD position and the application and selection process can be found here: https://euraxess.ec.europa.eu/jobs/416834
Applications must be submitted via the EDICT Doctoral Candidate Application Form – Fill in form by 30 March 2026 (23:59 GMT). Candidates may apply to up to five EDICT projects in order of preference.
Konw more : https://edictproject.eu
