Department: William Harvey Research Institute
Salary: £42,405 - £49,785 (Grade 5)
Reference: 950
Location: Charterhouse Square
Date posted: 18 January 2024
Closing date: 25 February 2024
Further details and apply
Overview
About the Role
Applications are invited for a motivated and committed bioinformatician with significant experience working with transcriptomics, particularly spatial or single-cell methods. The position is funded by the MRC and for an initial period of 18 months, and a substantial part of the work can be done through remote access to computational resources. The successful candidate will work with a novel human data set and study the interaction between skeletal aging and metabolic disease, integrating existing bulk and recently produced single-cell level spatial transcriptomics. Their role is to help establish informatic workflows for advancing methodologies for the identification of clinically informative subtypes of cells and work with the team to produce international quality research publications.
About You
The successful candidate will have PhD degree in bioinformatics, or significant post-doctoral experience with single-cell machine-learning methodologies. In particular they will be comfortable coding in Python and R, and have experience establishing informatics pipelines for the modelling of quantitative data. The ideal candidate will have a strong publication record in the field of transcriptomics (any medical topic) and a strong interesting in human ageing.
About the Team
The successful candidate will join a team at Queen Mary University London active in the fields of bioinformatics, transcriptomics, machine-learning, applied to ageing, metabolic and neurodegenerative diseases. Dr Timmons and Prof Slabaugh are part of an international collaborative team working on applying machine learning to human aging and age-related disease. Dr Timmons and colleagues at Duke and McMaster Universities have created a large-scale exon-level resource to model the human transcriptome and day to day apply network methodologies to model human neuromuscular aging. Professor Slabaugh’s team develop machine learning methodologies to biomedical data, particularly image-related, for the purpose of diagnosis, prognosis and discovery of therapeutic targets.
About Queen Mary
At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the previously unthinkable.
Throughout our history, we’ve fostered social justice and improved lives through academic excellence. And we continue to live and breathe this spirit today, not because it’s simply ‘the right thing to do’ but for what it helps us achieve and the intellectual brilliance it delivers.
We continue to embrace diversity of thought and opinion in everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.
This post is based between the Charterhouse Square and Whitechapel Campuses. It is full time appointment for 18 month with an expected start date in April 2024. The starting salary will be Grade 5 £42,405 - £49,785 per annum (pro-rata), depending on experience, inclusive of London Allowance.
Benefits
We offer competitive salaries, access to a generous pension scheme, 30 days’ leave per annum (pro-rata for part-time/fixed-term), a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and campus facilities including an on-site nursery at the Mile End campus.
Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly.
Further details and apply
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