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Location:
Saffron Walden, England, United Kingdom
Job reference: R-046296
Posted date: May. 31, 2019
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AstraZeneca 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. We're proud to have a unique workplace culture that inspires innovation and collaboration. We believe in the potential of our people and you’ll develop beyond what you thought possible.

The new R&D Oncology organisation brings together early and late oncology teams, from discovery through to late-stage development, with oncology specific Regulatory and Biometrics groups.

You’ll be in a global pharmaceutical environment but also exposed to strong rigorous academic science. For example, every postdoc has an external academic mentor to ensure we are working and publishing at the highest level in a field. What’s more, you’ll have the support of a leading academic advisor, who’ll provide you with the guidance and knowledge you need to develop your career.

This is a chance to work with leading AI and drug discovery scientists and have access to unique sets of proprietary data to assist in the identification of new drug molecules. AZ has a proven track record in the field of drug discovery driven by a focus on fundamental science. The project will be supervised by Dr Richard Ward and Dr Ola Engkvist. This is a unique opportunity to experience and benefit from both the industrial setting as well as the academic environment under the supervision of Dr Alpha Lee at the University of Cambridge. 

You’ll be expected to develop deep learning AI models to enable prediction of compound activity against a given target. We believe that our scientists are ideally positioned to harness such ‘Big Data’ in drug discovery with the support of our strong academic collaborators.

You’ll be immersed within a vibrant and productive chemistry group in a successful oncology drug hunting department as well as benefitting from a leading academic supervisor, Dr Alpha Lee from the University of Cambridge.

  • You’ll combine various internal and external data sources into an appropriate format to enabling the evaluation of machine learning models
  • You’ll utilise cutting edge deep learning methodology to exploit these data to construct models which are able to predict the activity profile of existing or novel molecules
  • You’ll develop novel approaches and methodology enabling the inclusion of protein structural information into deep learning models
  • You’ll drive the preparation of manuscripts to publish your findings
  • You’ll present your findings in suitable internal and external scientific meetings

Education and Experience required:

Essential:

  • BSc in chemistry or equivalent such as natural sciences or computer science (2:1 or above)
  • PhD relevant to the project (e.g. computational chemistry, theoretical chemistry, computational biology or machine learning research)
  • Fluency in the use of the Linux platform, including python and/or other programming languages
  • A proven record of productivity and problem-solving ability
  • Strong interpersonal, organisational and communication skills

Desirable:

  • Fluency in a machine learning framework such as Tensorflow or PyTorch
  • Knowledge of molecular modelling software packages
  • A proven record of work published in reputable scientific journals and presentations at scientific meetings
  • An interest in the practical application of predictive models in a drug discovery setting

Skills and Capabilities required:

As a Postdoc scientist in machine learning and drug discovery, you’ll:

  • Have an awareness of drug discovery and biology
  • Have the ability to collaborate with scientists across the organisation
  • Aim to publish in high-impact chemistry, chemical biology, and machine learning journals

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 – 31st May 2019 / Advert closing date – 10th August 2019

AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual 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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Postdoc Fellow - Target class artificial intelligence (AI) models
Scientific

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