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Statistical Geneticist / Genome Analyst,

Plats Royston, England, Storbritannien Jobb-id R-090774 Datum inlagd 09/21/2020

Statistical Geneticist / Genome Analyst, Centre for Genomics Research

Location: Cambridge

Salary & Package: Competitive

At AstraZeneca, we turn ideas into life changing medicines. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality.

Discovery Sciences

Discovery Sciences applies deep technical expertise in specialist technologies to support the delivery of targets and molecules to the early AstraZeneca pipeline. Targets are identified through our human genomics and functional genomics efforts, employing the latest technologies in genome editing and sophisticated cell model development. Once identified and validated, we work with therapy area project teams to identify novel small molecules effectors of these targets using our coordinated sample management and platform screening groups.

Our Genomics Research Centre

AstraZeneca’s Centre for Genomics Research (CGR) has an opportunity for a Statistical Geneticist or Genome Analyst to contribute to its Genomic Initiative. The Genomic Initiative includes the sequencing of participants from AstraZeneca clinical studies as well as analysing the sequence data from large population cohorts, including the 500,000 UK Biobank participants. Genomics is fundamental to our laboratory research, our clinical trials and the launch of new precision medicines. Our in-house clinico-genomic database is already among one of the largest globally, currently housing hundreds of thousands of human exome and genome sequences. These enable AstraZeneca to identify genetic determinants for disease risk, validate new targets for medicines and improve patient stratification opportunities among core areas of oncology, respiratory, cardiovascular, renal and metabolic disease.

This role represents an exciting opportunity to be part of ground-breaking research at the forefront of human genomics. Depending on the experience and interests of the job holder, this role will focus either on the development of innovative and robust statistical methods to analyse large-scale human genomics datasets (statistical geneticist), or more on the application of such methods and interpretation and communication of results (genome analyst). Job holders 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. The role will also work closely with specialists in translational science, drug discovery, pre-clinical modelling, and clinical development.


  • Coordinating and executing analyses
  • Apply genomic analyses to cohort studies to identify clinically relevant disease and response loci
  • Craft and develop algorithms and tools to explore relationships between genetic variation and patient disease and treatment outcomes
  • Support and refine the analysis framework and standard methodologies for variant interpretation
  • Assess the scientific and technical integrity of algorithms and tools within the analysis pipeline and work with development teams to add new tools to the pipeline
  • Provide detailed reports regarding the study design, analysis approach and research findings
  • Provide expert advice in a cross-functional teams with objectives focused on applying genomic analysis to drug discovery, including target identification, target validation and patient stratification
  • Maintain a well-developed knowledge of genomic science and technical advances in the international community
  • Contribute to publication of results
  • Ensure your own work, and work of team, is aligned with Good Laboratory Practice, Safety, Health and Environment standards, AstraZeneca standards and external regulations

Qualifications, Skills and Experience Required:


  • You will hold a PhD degree (or equivalent experience) in Bioinformatics, Biostatistics, Complex Trait Genetics, Computational Biology, Statistical Genetics or a related field (must be in quantitative field for Statistical Geneticist role)
  • Have experience in large-scale data analysis, applied statistics, and/or machine learning
  • Ability to communicate effectively with team members and non-experts, both verbally and through documentation
  • You will have an understanding or interest in the potential of genomics to impact drug discovery
  • Have the ability to prioritize, problem-solve and perform difficult tasks while under pressure
  • Possess excellent social skills and willingness to work within a team in a quickly evolving environment
  • You will have a track record of peer-reviewed publications in high-level scientific journals


  • Previous experience in a similar role
  • Solid postdoctoral (or equivalent) experience
  • Experience in case-control sequencing based statistical analyses
  • Experience in analysing whole genome sequencing data
  • Experience quantifying and interpreting the clinical relevance of rare variants
  • Familiarity with high performance and/or cloud computing
  • Coding skills appropriate for large scale genomics analysis
  • Familiarity working on genomics studies involving one of AstraZeneca’s core therapeutic areas
  • Experience interacting, curating, analysing and interpreting structured and unstructured electronic health data

How to Apply

If you would like to be considered for this opportunity please apply online before midnight on 22 Oct 2020.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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