Senior Research Associate in Bioinformatics

University College London - Great Ormond Street Institute of Child Health

We are looking for a researcher with an excellent track record and experience in bioinformatics and/or biostatistics. The postholder will be required to conduct and lead research in the area of bioinformatics and biostatistics of paediatric and/or adolescent disease, with a strong focus on rare diseases, and some focus specifically on paediatric and adolescent rheumatological diseases. The post holder will be based within the IIR Section in UCL GOS Institute of Child Health, but will work closely with teams in the ARUK Centre for Adolescent Rheumatology (which includes teams at both UCL GOS ICH and UCL Division of Medicine), and the NIHR GOSH BRC, Rare Disease Cohorts Theme.

The ARUK Centre for Adolescent Rheumatology is committed improving the health and well-being of adolescents with arthritis and other inflammatory rheumatological conditions, through basic and translational research; the Centre has generated significant large unique datasets (genetic, transcriptomic, proteomic and immunological in parallel with clinical data) to parallel the large patient cohorts, with age matched control data.

We are keen to attract candidates with an excellent research track record, experience in bioinformatics or biostatistics and a clear commitment to the clinical translation of their work for the benefit of patients. Evidence of leading and publishing research is essential. The Senior Research Associate will contribute to projects currently ongoing, support more junior colleagues in planning projects or analyzing data and will be encouraged to develop their own ideas and research projects within areas of strategic importance. The post holder is expected to develop and undertake new research studies, as well as contribute to teaching, supervising and mentoring junior staff.

The post is available and is funded for 4 years in the first instance.

A PhD or equivalent in a relevant subject eg biological sciences, natural sciences, computer science, mathematics or biostatistics is essential.

Experience of handling large and complex data sets eg GWAS/genotype, transcriptome, proteome, metabolome, large clinical datasets or other related/similar data, and publishing the results, will be essential. 

Experience of training and mentoring others would be desirable, as would successful previous applications for fellowships/ grant funding.

UCL vacancy reference:  1708007      

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button below.

If you have any queries regarding the vacancy please contact Professor Lucy Wedderburn on l.wedderburn@ucl.ac.uk or if you have any queries regarding the application process, please contact Madhur Sharma, ich.hr@ucl.ac.uk quoting job reference number.

Latest time for the submission of applications: 23:59

Interview Date: TBC

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