Post-doc, King’s College London (UK)

Statistical Genetics postdoc (3 years) at the SGDP Centre, King’s College London

Come and work with us on the next generation of Psychiatric Genomics Consortium studies, including depression anxiety and eating disorders. Full details below, email Cathryn Lewis (, Gerome Breen ( or Thalia Eley ( for further information.

Please forward to anyone who might be interested – open to all candidates, with support for visa applications from outside the UK.

Full details:

Statistical Genetics Researcher

Job ID: 037006 Salary: £38,304 – £40,414 per annum, including London Weighting Allowance Posted: 16-Nov-2021 Closing date: 14-Dec-2021Business unit: IoPPN Department: Social, Genetic & Dev Psychiatry MRC Contact details: Cathryn Lewis,

Job description

We are seeking an enthusiastic postgraduate with a PhD in statistical genetics, or a related analytical and computational field, to work in genetic studies of psychiatric disorders. In this exciting role, you will work with the international Psychiatric Genomics Consortium (PGC; ) across three disorders (major depressive disorder (MDD), eating disorders and anxiety) to identify the genetic underpinnings of these mental health disorders. Funded by the NIH to continue a decade of highly successful  PGC research, you will work with Cathryn Lewis, Gerome Breen and Thalia Eley in the Social, Genetic and Developmental Psychiatry (SGDP) Centre, and their research groups.

We strive to be a diverse research environment that is open, welcoming and supportive to all. Faculty-wide initiatives are supported by an active Diversity & Inclusion Team.  Our research groups are predominantly from white backgrounds, and we particularly welcome applications from individuals of any other race or ethnicity background (E.g. Black, Asian, Latinx).

The successful applicant will analyse genetic and clinical datasets shared with the Psychiatric Genomics Consortium and external datasets, such as UK Biobank. You will have the opportunity to collaborate closely with other statistical genetics analysts in the SGDP Centre, and internationally through the PGC.  You will be responsible for specific projects within the MDD, Eating disorders and Anxiety PGC working groups performing genome-wide association study (GWAS) analysis and applying post-GWAS methods.  Specific projects include polygenic score studies, identifying genetic predictors for treatment response, integrating environmental risk factors, dissecting genetic heterogeneity, and analysing dimensional measures of anxiety. These studies will provide the next generation of psychiatric genomics studies to uncover the genetic contribution to disorder risk and treatment response.

You will report to Professor Cathryn Lewis, working closely with other SGDP academics (Thalia Eley, Gerome Breen) and researchers within our teams to perform this research. The SGDP Centre is highly supportive of career development for postdoctoral researchers: you will have the opportunity to develop independence and support to apply for fellowship funding.  Experience with analysis of genetic studies is required, with high level statistical and computational skills.  Previous experience of psychiatric traits is not necessary.

This post will be offered on an a fixed-term contract for 3 years

This is a full-time post, but applications for a part-time role are welcomed

Key responsibilities

Key responsibilities  

•        Conduct genetic and genomic analysis of mental health data in MDD, eating disorders and anxiety in PGC and local studies

•        Engage in data management and data preparation to support other PGC analysts

•        Lead analyses and write scientific publications arising from the research, serving as first author

•        Work collaboratively with team members at the SGDP Centre and in the Psychiatric Genomics Consortium

•        Contribute to supervision of MSc and PhD students

•        Present results of analyses to team members, to the PGC, and at scientific conferences

•        Undertake reproducible analysis in an open science framework, developing analysis pipelines and using github repositories.