Research Fellow (0.6FTE)

About the job:

This is an exciting opportunity for an experienced, highly motivated individual to join our vibrant, multidisciplinary rare disease research team. Rare diseases affect ~475 million people globally, with more than 110,000 people affected by rare diseases across Northern Ireland. Recent rare disease initiatives by our team include the development of an online carer support tool, appraisals of the impact of socioeconomic factors, novel approaches for molecular diagnostics, building digital infrastructure to support diagnosis and care pathways, and the recently funded £12 million LifeArc Centre for the Acceleration of Rare Disease Trials (RD-TAP) with colleagues at the University of Birmingham and Newcastle University

You will work on epidemiology studies, harmonising multiomic data with associated analysis to support diagnosis and treatment of rare kidney diseases, and helping the team integrate diverse datasets. This cost-effective, carefully planned project will also provide excellent training and experience for a dedicated post-doctoral research fellow in a broad range of techniques. The post may involve liaising with international collaborators, generating new molecular data, collating and linking existing data, coordinating meetings and workshops, bioinformatic analysis of data, integrating datasets, preparing regular summary reports, and taking the lead writing academic outputs and research dissemination.

About the person:

Essential Criteria:

• Have or about to obtain a PhD in relevant discipline.
• Significant relevant research experience.
• Experience handling biological samples to generate human, blood-derived multi-omic data.
• Experience quality controlling and analysing multi-omic biological data.
• Experience analysing human health and social care datasets.
• Experience working with complex data management systems, integrating diverse data in a range of formats.
• Demonstrated experience of research methods and techniques pertinent to molecular epidemiology, longitudinal studies, and / or public health research.
• Experience of using data analysis packages such as R.
• Experience of project management, delivering research outcomes, and proven ability to work in a multi-disciplinary environment as part of a research team.
• A publication track record commensurate with the stage of career.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our website.

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