Publisher
source

Jessica Agnew-Blais

4 months ago

A Big Data Approach to Women’s Health Among Individuals with ADHD Queen Mary University of London in United Kingdom

Degree Level

PhD

Field of study

Neuroscience

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

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Country

United Kingdom

University

Queen Mary University of London

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Keywords

Neuroscience
Epidemiology
Psychology
Longitudinal Study
Health Science
Women's Health
Wearable Technology
Big Data
Neurodevelopment
Menopause
Quantitative Genetics
Medical Registry
Genetic
Remote Monitoring
Attention Deficit Hyperactivity Disorder
Menstrual Cycle
Statistic
Machine learning

About this position

This PhD project at Queen Mary University of London focuses on leveraging big data to address women’s health issues among individuals with ADHD, a neurodevelopmental disorder historically understudied in women. The project aims to improve outcomes for women with ADHD, particularly during periods of hormonal change such as puberty, the menstrual cycle, perinatal period, and menopause. Students may work with diverse data sources, including remote monitoring data from wearables and smartphone apps, genetic data for polygenic risk scores, and large population-based medical registries. Advanced statistical methods, such as intensive longitudinal data analysis and machine learning, will be employed.

The successful candidate will join Dr Jessica Agnew-Blais’s ADHD Life Lab, participating in lab meetings, cross-group sessions on child and youth development, and training opportunities both within Queen Mary and at other UK universities. The School of Biological and Behavioural Sciences offers a multidisciplinary research environment, access to state-of-the-art facilities, and support services. The PhD is part of a joint scholarship programme with the China Scholarship Council (CSC), covering tuition fees, living expenses, and a return flight for eligible Chinese applicants.

Applicants must be citizens and permanent residents of China, hold a Chinese passport, and meet all CSC and university eligibility criteria. A first or upper-second class honours degree in a relevant field (e.g., statistics, bioinformatics, data science, epidemiology, computer science, statistical genetics) is required; a master’s degree is desirable but not essential. Experience with statistics and/or data science is necessary, and candidates must meet English language requirements.

Applications must be submitted online by January 28, 2026, with all supporting documents. Shortlisted candidates will be interviewed, and successful applicants will receive a conditional offer pending CSC scholarship approval. The project offers opportunities to attend national and international conferences and develop advanced methodological skills in a leading UK research environment.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants must be citizens and permanent residents of the People’s Republic of China, hold a Chinese passport, and be applying for CSC funding. Candidates should have or expect to receive a first or upper-second class honours degree in a relevant area such as statistics, bioinformatics, data science, epidemiology, computer science, or statistical genetics. A master’s degree is desirable but not essential. Some knowledge or experience with statistics and/or data science is required. Applicants must meet the IELTS requirements for the course and upload evidence before the CSC application deadline, ideally by March 1, 2026. All required documentation, including CV, personal statement, English language certificate, academic transcripts, degree certificates, and references, must be submitted.

How to apply

Submit a formal application through the Queen Mary online form by January 28, 2026, identifying yourself as a 'CSC Scholar' in the funding section. Upload all required documents including CV, personal statement, English language certificate, academic transcripts, degree certificates, and references. Shortlisted applicants will be invited for a formal interview. After receiving a QMUL Offer Letter, apply to CSC for the scholarship with supervisor support.

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