Postdoctoral Research Associate

Location
London (Greater) (GB)
Salary
£38,826 per annum, including London Weighting Allowance
Posted
10 Jun 2022
End of advertisement period
20 Jul 2022
Ref
047905
Contract Type
Fixed Term

Job description

We are seeking an enthusiastic postgraduate with an interest in the biology of mental health and PhD in genetics, computer science, or a related analytical field. The successful applicant will conduct fine-mapping analyses to identify causal genetic variants (including common and structural variants) in major depressive disorder and validate these results in sequence data from the UK Biobank.  

The successful applicant will report to Dr Jonathan Coleman and will form part of his expanding research group focussed on linking statistical genetics to biology in mental health disorders. The group is based in the Social, Genetic and Developmental Psychiatry (SGDP) Centre, part of the Institute of Psychiatry, Psychology and Neuroscience. We collaborate extensively with other research groups examining the statistical genetics of mental health disorders, both at the SGDP and internationally. Particularly, the successful applicant will work closely with Dr Alfredo Iacoangeli and his bioinformatics group to extend analyses and examine structural variants. 

The successful applicant will conduct research building on recently identified associations between genetic variants and major depressive disorder. You will work closely with the supervisor to expand an existing fine-mapping pipeline and apply it to the latest genetic data on major depressive disorder from the Psychiatric Genomics Consortium. You will collaborate with colleagues in bioinformatics and with the statistical genetics community at the SGDP Centre, and will consult with cell biologists at the wider Institute of Psychiatry, Psychology, and Neuroscience. These analyses will further our understanding of the biology of major depressive disorder, a fundamental step in improving future treatments. 

The SGDP Centre strives to provide a diverse research environment that is open, welcoming and supportive to all. Faculty-wide initiatives are supported by an active Diversity & Inclusion Team.  We particularly welcome applications from individuals identifying with identities and backgrounds under-represented in academia.

 

This post will be offered on a fixed-term contract for 12 months 

This is a full-time post - 100% full time equivalent, but applications for a part-time role are welcomed.

 

Key responsibilities

•        Conduct fine-mapping analyses of major depressive disorder in genome-wide genotype data from multiple cohorts.  

•        Conduct imputation to obtain data on short tandem repeats and analyse this data.

•        Assess variant associations in sequence data.

•        Interact with collaborators to obtain data for analyses.

•        Present results of analyses to the supervisor, collaborators, and other team members. 

•        Contribute to writing scientific publications from the research  

•        Undertake reproducible analysis within an open science framework.  

 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Skills, knowledge, and experience

Essential criteria  

1.       PhD in statistical genetics, computer science, or an allied academic area. 

2.       Experience working with human genome-wide genotype data and/or human sequence data 

3.       Experience working in a UNIX/POSIX computing environment 

4.       Experience of working in R 

5.       Demonstrated commitment to conducting open science through using reproducible analysis pipelines 

6.       Ability to work both independently and as part of a team 

7.       Excellent attention to detail in data management and reporting results 

8.       Strong interpersonal and written communication skills, with ability to discuss research findings 

 

Desirable criteria

1.       Interest in mental health research 

2.       Knowledge of functional and regulatory biology 

3.       Experience of fine-mapping analyses 

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