At least 3 years of proven research experience in bioinformatics and the analyses of ‘omic’ data coupled with socio-economic and/or health data.
• Proficiency in programming with R, Python, UNIX/shell scripts as well as the ability to build new tailored pipelines.
• Strong background in quantitative statistical analysis of large-scale cross-sectional and longitudinal datasets.
• Good knowledge of the basic concepts of epidemiology.
• Working knowledge of statistical and data analysis software packages e.g. SPSS, STATA, R, Mplus.
• Candidates must have a strong publication record.
• Ability to work on own initiative but also to work as an active and efficient team
member when required.
• Experience with DNA methylation data, epigenome-wide association studies (EWAS) and generation of epigenetic clocks. (desirable)
• Experience in a similar academic and research environment (desirable)
• Knowledge of College structures and procedures would be an advantage (desirable)
Strong organisational skills, ability to judge priorities, multitask and work to tight deadlines.
• Highly self-motivated, able to work independently and organise own workload.
• Ability to work accurately, with attention to detail.
• Excellent communication and interpersonal skills: ability to work with a large multi-disciplinary team, be able to integrate and become an effective team member as quickly as possible and provide feedback on the assigned tasks when required.
• Documentation and writing skills: deliver the necessary documentation and reports in a clear and concise manner which is understandable to both non-technical and research staff.
• A flexible approach and willingness to undertake other duties as necessary.
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