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HDR-UK Post-Doctoral Fellow (Genetics of Rare Disease)

Wellcome Sanger Institute

Grade: PDF

Contract Length: 3 years
Now is an extremely exciting time for the study of the genetic causes of rare disorders. Whole genome sequencing of large patient cohorts allows the identification of novel genetic causes of disease. Increasing accessibility of routine healthcare data on sequenced patients enables deeper characterization of disease phenotypes. Integration of these two rich and complementary sources of data promises to revolutionise our understanding of genetic causes of disease. This fellowship draw together UK strengths in genome sequencing and health data research. In partnership with Genomics England and Health Data Research UK, and working alongside the Hurles group at the Wellcome Sanger Institute, you will analyse whole genome sequencing data on thousands of rare disease families for which rich electronic health data are already available.

About the Research:

Genomics England, in partnership with the UK National Health Service, has coordinated the 100,000 Genomes Project, which includes over 70,000 genome sequences from rare disease families, and are continuing to sequence rare disease families as part of routine diagnostic practice, and make these data available to researchers. Health Data Research UK (HDR-UK) is the UK’s national health data research institute, focused on mobilising, curating and analysing electronic health records (EHRs).  You will work with the rich genetic and clinical data within the Genomics England research environment and integrate these data with other research studies (e.g. the DDD study), and will be able to leverage the expertise in EHR analysis within the wider HDR-UK.

About the Role:

You will work alongside Matt Hurles's group at the Sanger Institute, which includes experimental human geneticists as well as bioinformaticians and statistical geneticists. Our current focus is on harnessing genomic technologies, such as exome and genome sequencing, to identify novel disease-causing variants and to model these variants in cellular models. Our rare disease research focuses on developmental disorders, either identified prenatally (by ultrasound), or postnatally (through pediatric cardiology and clinical genetics). We integrate large datasets from multiple studies (e.g. 100,000 Genomes Project, DDD, PAGE) to maximise the power to generate novel insights into the genetic architecture of rare diseases.This fellowship is focused on understanding genetic causes of rare diseases by analyzing linked genetic and EHR data, primarily from the rare disease arm of the 100,000 Genomes Project. Data are available for a wide range of different rare diseases, and a broad range of research questions are applicable. You will have the opportunity to undertake analyses across a range of rare diseases.

About You:

You should have a PhD and a track record in Statistical/Computational Genetics with an interest in harnessing deeper phenotypic data. Strong data analytical skills are essential. Experience with computational phenotypic analysis would be desirable. We are seeking a creative, independent, highly-motivated and productive individual. Our work is highly collaborative and integrative. You will be encouraged to articulate and develop your own research projects. There will be opportunities to develop collaborative projects among the partner organisations, and to foster a growing community of researchers working on genetic and EHR datasets.

Essential Skills
  • PhD in statistical/computational genetics 
  • Demonstrably strong data analytical skills 
  • Ability to work collaboratively 
  • Effective communication skills within the team and with collaborators 
  • Efficient time management 
  • Experience of preparing manuscripts for publication 
  • Experience of statistical analysis of large genetic datasets 
  • Interest in analysis of electronic healthcare data 
  • Ability to work collaboratively with a range of stakeholders at all levels 
  • Effective communication skills within the team and with collaborators 
  • Efficient time management 
  • Demonstrates inclusivity and respect for all 

Other information

Please apply with your CV and a cover letter outlining your suitability for the role addressing the criteria set out above and in the job description.

Download Job description

Location: Cambridge, Hinxton
Salary: £32,780 to £41,093 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 8th October 2021
Closes: 9th November 2021
Job Ref: 84484
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