We’re currently looking for talented scientists to join our innovative academic-style Postdoc program. From our centre in Cambridge, you’ll be in a global pharmaceutical environment, contributing to live projects right from the start. You’ll take part in a comprehensive training programme, including a focus on drug discovery and development, given access to our existing Postdoctoral research, and supported to pursue your own independent research in state of the art laboratories. It’s a newly fast-growing programme spanning a range of therapeutic areas across a wide range of disciplines.

What’s more, you’ll have the support of a leading academic advisor, who’ll provide you with the guidance and knowledge you’ll need to develop your career. This is an exciting area that hasn’t been explored to its full potential, making this an opportunity to make a real difference to the future of medical science.

AstraZeneca (AZ) is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies. At AZ, we’re proud to have a unique workplace culture that inspires innovation and collaboration. Here, employees are empowered to express diverse perspectives – and are made to feel valued, energised and rewarded for their ideas and creativity.

Our Discovery Sciences team operates from truly state-of-the-art centres spanning the UK, US and Sweden. You’ll work with some of the most knowledgeable technology experts in the industry, all collaborating on high-profile drug discovery projects. Cancer is one of the greatest challenges facing medical science today.

The position is within Bioinformatics team, working to develop advanced machine learning models capable of predicting cancer drug resistance. The emergence of drug resistance is an almost universal phenomenon in the cancer treatment paradigm. Understanding which genes are complicit in the development of resistance allows the possibility of adopting therapeutic strategies to either prevent or treat drug resistant cells. In addition to providing an exciting and steadily growing large-scale dataset exploring drug resistance using genome-wide CRISPR/Cas9 screens, AZ is offering expert domain knowledge in cancer resistance and the opportunity of getting hypotheses directly experimentally validated and thereby enabling high-impact publications.

This position will be in multi-disciplinary collaboration between AZ Discovery Sciences and Oncology, Prof. Dr. Julio Saez-Rodriguez’s group at Institute for Computational Biomedicine Heidelberg University / EMBL-EBI, and Dr. Michael Menden’s group for Systems Biomedicine at the Institute of Computational Biology – Helmholtz Centre Munich.

Accountabilities and Responsibilities:

  • Work independently to plan and carry out research in accordance with the project aims.
  • Robustly clean and integrate data from internal and external sources to engineer the best features for machine learning training. A strong focus on cancer biological relevance will be required.
  • Develop and implement machine learning models.
  • Ensure that results, models and codes are scientifically robust and documented.
  • Scientifically assess the performance of models, feature impact and build confidence indexes.
  • Proactively engage with other members of the group, internal and external collaborators to discuss results.
  • Write-up and publish work in peer-reviewed Journals.
  • Present findings at conferences as well as in AZ.

Education and Experience requirements:


  • PhD in Bioinformatics, Chemoinformatics, Computer Science, Mathematics, Statistics, Data Science, Engineering or similar.
  • A solid understanding of statistical and mathematical principles for biological data analysis.
  • Experience applying machine learning methods in a systems biology or systems medicine context.
  • Deep knowledge of at least one of the following areas: deep learning, network/graph analysis, NGS/RNAseq data analysis, cancer drug resistance.
  • Programming proficiency and experience with relevant software tools such as R, Python.
  • Working in a Linux environment, with experience of cluster or cloud computing


  • Experience in CRISPR screen analysis
  • Experience in high-throughput screens and pharmacogenomics analysis

Skills and Capabilities required:

  • Positive can-do attitude and eager to learn in each interaction.
  • An enthusiasm to explore non-traditional approaches to bring big data together in biologically meaningful ways.
  • Excellent communication and presentation skills, including experience in communicating across discipline boundaries

This is a 3 year programme.  2 years will be a Fixed Term Contract, with a 1 year extension which will be merit based.  The role will be based in Cambridge, UK with a competitive salary on offer. To apply for this position, please click the apply link below.

Advert opening date – 11th October 2018 / Advert closing date – 22nd November 2018

AZ is an equal opportunity employer. AZ will consider all qualified applicants for employment without discrimination on grounds of disability, gender or gender orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.

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