About us The post will be based in the KCL Social, Genetic, and Developmental Psychiatry Centre, within the Institute of Psychiatry, Psychology and Neuroscience (IoPPN).
The centre offers a diverse research environment that is open, welcoming and supportive to all. The faculty-wide initiatives are supported by an active Diversity & Inclusion Team.
The Social, Genetic & Developmental Psychiatry (SGDP) Centre is uncovering the genetic and environmental influences on mental health and psychiatric disorders. Our research encompasses behavioural genetics, molecular genetics, experimental psychology and psychiatry, and neuroimaging. Scientists at the SGDP lead some of the UK's foremost longitudinal cohort and twin studies including TEDS, eRISK, Dunedin, IMAGEN and GLAD.
The NIHR BioResource Centre Maudsley leads the NIHR BioResource for Mental Health. We focus on recruiting participants experiencing mental health conditions, as well as healthy people.
Alongside GLAD MHG and The GLAD study, Prof. Breen's team boasts an accomplished portfolio of clinical and genetic studies which aim to improve treatment and outcomes for those affected by anxiety, depression, eating disorders and other mental health conditions.
About the role We are seeking a highly motivated postdoctoral Research Associate in research data science and analysis to join Professor Gerome Breen's internationally recognised team at King's College London. This post will support the delivery of the Genetic Links to Anxiety and Depression - Mental Health Goals (GLAD-MHG) Omics Cohort, one of the UK's most ambitious precision psychiatry initiatives, hosted within the NIHR BioResource Centre Maudsley.
Despite being a leading cause of disability worldwide, Major Depressive Disorder (MDD) is an underserved market segment with significant unmet medical need, GLAD MHG will leverage proven success and substantial investment from KCL, Maudsley and NIHR BioResource in the GLAD study to create a trial-ready dataset integrating detailed phenotyping, multi-omics, and medical records to support MDD precision psychiatry.
The GLAD Study is the largest anxiety and depression project ever undertaken. The study is part of the
National Institute of Health Research (NIHR) BioResource . It is led by researchers at King's College London, in collaboration with researchers at Ulster University, University of Edinburgh, and Cardiff University. GLAD was launched in September 2018, and over 30,000 participants have fully enrolled.
This role offers the opportunity to work with one of the world's largest, deeply characterised mental health cohorts, and will be integrated with the highly supportive departmental environment of the Social, Genetic, and Developmental Psychiatry Centre. You will be applying cutting-edge
multi-omic, AI, and data science approaches to address urgent challenges in major depression. The successful candidate will have formal mentoring and gain experience at the interface of academia, healthcare, and industry, contributing to discoveries that shape the future of precision psychiatry.
This is a full-time (35 hours per week), and you will be offered a fixed term contract for 2 years with the possibility of extension; earliest start date 1st of April 2026.
Research staff at King's are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information.
About you To be successful in this role, we are looking for candidates to have the following skills and experience:
Essential criteria - PhD qualified in biostatistics, statistics or related field (or pending results)
- Proficient in using R, Python or similar programming language
- Experience of working with clinical or equivalent data.
- Experience in developing analytic pipelines.
Desirable criteria - Experience of working within Trusted Research Environments to analyse data.
- Good presentation and communication skills
- Experience or interest in Major Depressive Disorder (MDD) or general mental health disorders.
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.
* Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.
Further information We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.
We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.
As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities.
We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.
To find out how our managers will review your application, please take a look at our ' How we Recruit' pages.
This post is subject to Disclosure and Barring Service and Occupational Health clearances.
We reserve the right to close this advert early if we receive a high volume of applications.