Senior Research Associate

Overview

In this role you will apply bioinformatic analyses to multi-omic datasets to identify biomarkers for hepatocellular carcinoma risk and treatment response. You will integrate clinical data within a secure research environment to support biomarker discovery, risk stratification, and early detection efforts as part of a multidisciplinary cancer research team. Your work will advance translational aims through data-driven insights and reproducible code, contributing to high-impact publications.

Pay / Benefits

• generous holiday package
• pension schemes
• health and wellbeing initiatives
• opportunity to buy additional holiday
• competitive salary
• career development opportunities

Responsibilities

• Lead bioinformatic analyses across SNPs, RNAseq, serum proteomics, WSI, and spatial data, integrating clinical information
• Ensure safe, secure storage and deposition of large datasets in online repositories; support CRH-led data infrastructure
• Maintain and contribute to REDCap database of clinical trial data for liver cancer treatments
• Create, maintain and share version-controlled code/notebooks to enable reproducible analyses
• Collect, analyze and interpret research data; draw conclusions to inform project objectives
• Coordinate work with clinicians and researchers; solve problems to advance research aims
• Disseminate findings through conferences and publications; contribute to project dissemination materials
• Mentor junior colleagues; develop methodological and technical skills within the team
• Define methodologies for research and identify opportunities for further investigations; contribute to grant applications
• Lead ideas to enhance technical approaches and data analysis within the project

Key requirements

• Experience analyzing spatial and quantitative relationships in high-content multiplex histopathology images
• Advanced statistical modelling of high-dimensional data; experience with penalised models and machine learning
• Demonstrated understanding of RNAseq and gene expression analysis
• Experience analyzing serum proteomic data (e.g., OLINK, SOMASCAN)
• Experience handling securely large bioinformatic datasets
• Knowledge of liver cancer staging, treatments, and predictive biomarkers
• Attention to detail and high accuracy in analyses
• Ability to present complex information clearly to diverse audiences
• Proven data analysis and results reporting skills
• Experience collaborating with colleagues and mentoring junior staff
• Excellent IT skills across major office applications
• Ability to work with initiative and creative problem solving
• Understanding of the research environment and high analytical capacity
• Ability to communicate complex information clearly and publish or present findings
• Proven experience presenting at conferences or in publications

• collaboration
• mentoring
• communication
• RNAseq analysis
• RNA gene expression analysis
• spatial data analyses

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