This role is an opportunity to be part of ground-breaking research at the forefront of human genomics.

This role will focus on the development of innovative and robust statistical methods to analyse large-scale human genomics datasets, and/or on the application of such methods and interpretation and communication of results.

You will be part of a dynamic team in CGR’s multidisciplinary genomics research environment comprising bioinformaticians, computational biologists, genome scientists, software engineers, postdoctoral researchers, disease area specialists.

You will also work closely with specialists in translational science, drug discovery, pre-clinical modelling, and clinical development.

• Lead and carry out quantitative genomic analyses on large-scale cohort studies, to identify risk and response associations for diseases of interest

• Deliver novel insights into the biology of disease, validation of new targets for medicines and the improvement of selection of patients for clinical trials

• Incorporate additional molecular data into genomic analyses such as gene expression data, metabolomics and/or proteomics

• Work with sophisticated phenotype data (e.g., electronic health records and clinical trials) to better identify population subgroups of greatest interest

• Develop analytical algorithms and tools to address scientific questions with big data

• Contribute to publication of results

• Support and supervise more junior team members

• Ensure all work is follows Good Laboratory Practice, Safety, Health and Environment standards and all internal AstraZeneca standards and external regulations

• Doctoral degree (or equivalent experience) in bioinformatics, biostatistics, complex trait genetics, computational biology, statistical genetics or a related field

• Have experience in large-scale genetic data analysis, applied statistics, and/or machine learning

• Coding skills appropriate for large scale genomics analysis

• Understanding or curiosity about the potential of genomics to impact drug discovery

• Possess superb communication skills and willingness to work within a team in a quickly evolving environment

• Have a track record of peer-reviewed publications in high-level scientific journals

Desirable Criteria

• Experience in analysing genome sequencing data

• Experience in case-control sequencing based statistical analyses

• Familiarity with high performance and/or cloud computing

• Experience curating and analysing electronic health data

• Experience quantifying and interpreting the clinical relevance of rare variants