Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by symptoms of inattention, hyperactivity and or impulsivity. The diagnosis and monitoring of the symptom severity are mostly based on subjective reports, while neuropsychological testing and direct classroom observations are more objective diagnosis methods, but they are time-consuming and expensive. A new cost-effective and accurate diagnosis and symptom monitoring technique is urgently needed.
This project aims to explore whether EEG can provide a quantitative and effective approach for the diagnosis and severity monitoring of ADHD. Additionally, we would like to evaluate whether an integration of advanced signal processing, network analysis and deep learning techniques would improve the diagnosis performance compared with traditional EEG analysis methods.
The successful applicant will be awarded a scholarship from Coventry University with the supervision team being drawn from Coventry University and Deakin University, Australia. The PhD Student will graduate with two testamurs, one from Coventry University and one from Deakin University, each of which recognizing that the program was carried out as part of a jointly supervised doctoral program. The program is for a duration of 3.5 years (funding only for 3.5 years, maximum allowed time 4 years) and scheduled to commence in September 2024. The PhD Student is anticipated to spend up to 12 months of the total period of the program at Deakin University, with the remainder of the program based at Coventry University.
Training and Development
The successful candidate will receive comprehensive research training including technical, personal and professional skills.
All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.
Applicants must meet the admission and scholarship criteria for both Coventry University and Deakin University for entry to the cotutelle programme.
OR
The potential to engage in innovative research and to complete the PhD within a prescribed period of study
The applicant is required to submit a supporting statement as part of their application. Within the supporting statement, candidates should articulate why they believe they are suited for this position. Specifically, we anticipate that the applicant will demonstrate some experience/and or knowledge pertinent to machine learning and will have good programming skills.
For further details please visit: https://www.coventry.ac.uk/research/research-opportunities/research-students/making-an-application/research-entry-criteria/
https://www.coventry.ac.uk/research/research-opportunities/research-students/making-an-application/
To find out more about the project please contact Dr Fei He: fei.he@coventry.ac.uk
All applications require a covering letter and a 2000-word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project.
To help us track our recruitment effort, please indicate in your email – cover/motivation letter where (globalvacancies.org) you saw this job posting.
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