Senior Bioinformatics Scientist, Functional Genomics, AstraZeneca Oncology R&D

  • AstraZeneca
  • Cambridge CB23, UK
  • 11/02/2020
Full time Data Science Data Analytics Big Data Statistics

Job Description

Senior Bioinformatics Scientist, Functional Genomics, AstraZeneca Oncology R&D

Cambridge, UK

Description

AstraZeneca is a global, ground-breaking biopharmaceutical company. We are dedicated to discovering, developing, and delivering innovative, meaningful medicines and healthcare

solutions that enrich the lives of patients. The vision of AstraZeneca Oncology is to redefine cancer, redefine our solutions to cancer, and restore patients' lives. Would you like to be part of this vision?

The Computational Oncology team has expertise in production informatics, bioinformatics and data science and works with our oncology drug project teams throughout the discovery pipeline, from new target discovery to late stage clinical trials.

We are currently seeking an experience, motivated Bioinformatician with expertise in the

genomics of cancer to join the team in the joint AstraZeneca – Cancer Research UK

Functional Genomics Centre (FGC). The FGC is a recently formed world-leading centre of

expertise in genetic screens, cancer models, CRISPR vector design and computational

approaches to big data. Its goal is to identify novel targets and resistance mechanisms to

create new cancer medicines!

The post holder will work within the FGC across AstraZeneca Oncology drug projects to

deliver large scale functional genomic profiling data analyses to support the discovery of

novel targets. In addition, you will develop and combine ground-breaking tools in the

cloud-based FGC Analytics Pipeline for the analysis of screening data from different CRISPR technologies, aligning with the wider AstraZeneca data strategy.

Continuous support and training will be provided for the individual to develop deep specialist knowledge and skill set in the centre’s areas of focus.

Accountabilities/Responsibilities

To be successful in this role, you will:

  • Work as part of the AstraZeneca Functional Genomics Centre team in yielding insights from genomewide CRISPR knockout/in data. This will support the characterisation of the genomic landscape of novel targets to overcome resistance to treatments and identify new drug combinations.
  • Liaise with drug project science teams to address their scientific and technical challenges involved with progressing new CRISPR screen-based targets through to target selection.
  • Lead the development and application of standardised bioinformatic approaches to the analysis, storage and interpretation of functional genomics data via the FGC Analytics Pipeline.
  • Assess data analysis protocols for novel techniques such as single cell CRISPR screening
  • Collaborate with the AstraZeneca Biological Insights Knowledge Graph team to utilise AI in triaging CRISPR based hits based on the world’s knowledge.
  • Build and steer development of tools from prototype to production for bench scientists to access and visualise project data
  • Build collaborations within industry and academia to find the most effective solutions to our drug discovery problems, for example within the Cancer Dependency Map Consortium publish your work in high impact journals.

Requirements

Education:

You will have a relevant PhD qualification (or equivalent graduate degree plus proven applied experience), combining:

  • Technical expertise in either bioinformatics, data science, computational biology or similar
  • A deep understanding of the genetics/genomics of cancer

Essential:

Expertise in the analysis of genomic data covering data QC, handling, processing &

interpretation.

Python and R programming expertise in a Unix environment with track record of contributions to open source projects on platforms such as GitHub.

Analytics pipelining expertise utilising orchestrators such as NextFlow.

Understanding of data and metadata capture and sharing via databases.

Knowledge of cancer genetics and key algorithmic & statistical methods applicable to cancer genomics.

Skilled in effective requirements gathering, communication and key messaging of complex data to non-experts. Effective contributions to collaborative projects / products involving cross-disciplinary and global teams.

Desirable:

Knowledge of pooled CRISPR screening (or RNAi) data analysis.

A detailed understanding of the contribution of bioinformatics to drug discovery.

Expertise in the development of novel statistical approaches for the analysis of biological

data.

Well networked within external bioinformatics and oncology communities.

An excellent publication track record.

Awareness of graph modelling, machine learning, artificial-intelligence, Bayesian analytics or other non-traditional approaches to model biological data.

Please apply now, to join us on our path to change the way new targets are identified for

curing cancer!!!