Research Assistant – Predicting OCD Onset (with PhD studentship pathway) – Strand, London, WC2R 2LS
About us:
King’s College London’s Institute of Psychiatry, Psychology & Neuroscience is a global leader in mental health research. The Department of Child and Adolescent Psychiatry leads international collaborations on early detection and prevention of neuropsychiatric disorders. This position sits within the King’s Maudsley Partnership for Children and Young People, bridging academic research and NHS implementation.
NB: The associated PhD studentship funding covers UK Home tuition fees only. Applicants who are liable for Overseas tuition fees will be responsible for meeting the difference between the Home and Overseas fee rates. Candidates invited to interview may be asked to demonstrate a realistic means of covering this additional cost before enrolment onto the PhD programme.
About the role:
King’s College London is seeking a Research Assistant to join a Wellcome Trust-funded programme predicting obsessive-compulsive disorder onset across cohorts in the UK, Brazil and Sweden. Based in the Department of Child and Adolescent Psychiatry at the IoPPN, you will harmonize rich clinical and behavioural data from nine longitudinal cohorts totalling around 90,000 participants and support the development of machine learning survival models that predict the onset of OCD in children and young people. The post offers a distinctive career pathway: as well as a five-year Grade 5 salaried position, the successful candidate will receive funded PhD tuition and undertake doctoral research embedded in the project. You will work closely with Professors Shaw and Sudre within the King’s Maudsley Partnership for Children and Young People, gaining expertise in predictive modelling, multi-cohort data harmonization and developmental psychopathology. The successful candidate will bring strong analytical skills, a keen interest in youth mental health research, and be motivated to develop an academic career.
This is a full-time post (35 hours per week), and you will be offered a fixed term contract until 30th April 2031.
About you:
To be successful in this role, we are looking for candidates to have the following skills and experience:
Essential criteria
- MSc (Distinction or Merit) in neuroscience, psychology or a closely related discipline.
- Direct experience of clinical research data collection with young people, including administration of structured interviews, questionnaires or behavioural tasks, to enable critical evaluation of data provenance and quality during cross-cohort harmonization.
- Experience integrating and cleaning multimodal datasets combining behavioural tasks, self-report measures and clinical assessments.
- Demonstrated ability to design and implement a machine learning analysis pipeline on psychiatric or clinical data, working largely independently.
- Programming experience in Python and/or R for data processing and statistical modelling, with willingness to extend skills to survival analysis and harmonization methods.
- Demonstrated ability to work effectively within a multidisciplinary research team, including the capacity to incorporate feedback from colleagues with diverse technical and clinical expertise.
- Excellent organizational skills and meticulous attention to data quality and documentation.
- Strong scientific communication skills, evidenced by presentations or manuscript contributions.
Desirable criteria
- Publication or submitted manuscript from masters or subsequent research.
- Experience with neuroimaging or genomic data.
- Interest or experience in OCD, anxiety or related disorders in young people.
- Valid Good Clinical Practice certificate or willingness to obtain within three months of appointment.
- Awareness of data governance and GDPR requirements for handling sensitive health data.
Downloading a copy of our Job Description
Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process.
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