Research Assistant in Multiomic Data Analysis

Experimental Medicine

Location: Guildford
Salary: £32,982 to £34,980 per annum
Fixed Term (- 30/09/2024)
Post Type: Full Time
Closing Date: 23.59 hours BST on Wednesday 22 November 2023
Reference: 043923-R

As part of the British Heart Foundation project focussed on omics approaches to identify regulators of vascular remodelling in pulmonary hypertension, we offer an exciting position at the Faculty of Health and Medical Sciences, University of Surrey, to work within the group of Prof Inga Prokopenko, PhD and within the Section of Statistical MultiOmics as well as within the People-Centred AI institute. This role will focus on large-scale multiomic data analyses available for the large UK-based study for pulmonary hypertension with major focus on epigenome-wide association study (EWAS) analyses and combining of such information with proteomic data, clinical characteristics and other layers of data.

Pulmonary arterial hypertension (PAH) is a rare condition characterised by pulmonary vascular remodelling leading to premature death from right heart failure. We performed a pilot study of blood DNA methylation analysis of PAH patients from a UK PAH Cohort. We gained access to available data from further controls from two distinct studies using the same Illumina IScan-EPIC 800k array chip, with analyses indicating baseline associations between methylation status and PAH diagnosis. One of the lead candidates is a CpG near the CTSZ gene, encoding a lysosomal cysteine proteinase cathepsin Z expressed ubiquitously in cancer cell lines and multiple tumours, which can interact with integrin-β3 activating FAK/Src signalling. How DNA methylation patterns alter over time in response to therapy and in other forms of PH has yet to be established.

The data from serially sampled PAH patients will allow analyses of the relationship between dynamic changes in DNA methylation status and clinical phenotypes as detailed above. We will further expand the DNA methylation analyses to other forms of PH (e.g. secondary to lung disease, heart failure or thromboembolism) using 100 disease controls and 300 PH patients of mixed aetiologies using the established pipelines (The CPACOR pipeline - published by Lehne et al. was used for the processing on genome build GRCh37/hg19, quality control (QC) and normalisation of the raw methylation data). Such an expanded EWAS analysis would allow the determination of the specificity of identified changes to PAH and further the definition of methylation patterns identifying and co-occurring in other presentations of PH.

About you

We are seeking candidates with expertise in an area pertinent to the project and experience in advanced statistics, machine learning, data integration, software development, sensor/wearable/mobile data, programming using C++/Python, and/or biomedical informatics. The successful candidate is expected to be able to organise his/her work with minimal supervision and prioritise work to meet deadlines of the project. Due to active collaborative interaction within this project, advanced oral and writing English knowledge are required.

What we can offer

In addition to your salary, you will receive pension contributions, a generous annual leave entitlement, relocation assistance where appropriate, an attractive research environment, and access to a variety of staff development opportunities. Furthermore, our benefit packages include childcare assistance and discounted membership to University sports facilities.

How to apply

To apply for this role, please submit your CV and a cover letter addressing the major requirements of the post.

If you would like to discuss your interest in this role, please contact Prof Inga Prokopenko directly via email i.prokopenko@surrey.ac.uk

The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all.  We place great value on diversity and are seeking to increase the diversity within our community.  Therefore we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities.

Further details:    Job Description