PhD Studentship: Developing Digital Tools for Personalized Preventative Pathways in Children's Mental Health

3 days ago


Cambridge, Cambridgeshire, United Kingdom University of Cambridge Full time
Job Title:

PhD Studentship: Developing Digital Tools for Personalized Preventative Pathways in Children's Mental Health

Job Description:

Based within the Timely Research Group, Department of Psychiatry, University of Cambridge, we are seeking a highly motivated PhD student to contribute to the development of digitally supported personalized prevention pathways for children's mental health services.

The successful candidate will be part of a vibrant research team and will have the opportunity to work on a cutting-edge project that aims to refine a blueprint for a preventative pathway, co-develop detailed specifications for AI-driven digital tools, and investigate the role of heterogeneous factors in neurodevelopmental and mental health conditions.

We are particularly interested in candidates who would like to use large longitudinal datasets to investigate how factors contribute to differences in neurodevelopmental and mental health conditions. As a part of the PhD, candidates will build complex longitudinal models to investigate the correlation and interaction of various factors, and develop responsible AI tools that are equitable and do not exacerbate or create bias in the delivery of care.

The University of Cambridge is committed to equality, diversity, and inclusion and encourages applications from all sections of society. The successful candidate will have the opportunity to work in a dynamic and supportive environment, with access to state-of-the-art facilities and a range of training and development opportunities.

To apply, please submit an academic CV, a research proposal within this research area (maximum 2000 words, excluding bibliography or figures), and a cover letter indicating a brief summary of your research interests, any completed research conducted, interests and skills in statistical methods, analyses of large datasets, and coding, and a clear statement of your eligibility for this funding award.

Applications must be received by midnight on 30 November 2024. Interviews will be held within a month of the application deadline.



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