AI in Drug Design

Beatson Drug Discovery Unit

Starting Salary from £31,604 to £41,929 (Depending on experience) plus relocation allowance where appropriate
Initial 3 year fixed term contract (with possibility of up to 2 year extension)

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The Beatson Drug Discovery Unit (BDDU) is an integrated, industry-standard drug discovery group translating basic biology research from the Beatson Institute and other CRUK centres into medicines for the treatment of cancer.


Recently, deep generative models have become a very lively research field in drug design, their main aim is to create novel chemical compounds with desirable chemical and pharmacological properties using deep neural networks. Their evolution could open new frontiers for intelligent molecular generation and optimization. We are seeking to hire a postdoctoral data scientist who will apply these ground-breaking deep learning techniques to active drug discovery projects.


You will play a crucial role in the creation and onboarding of BDDU's artificial intelligence capabilities and techniques applied to drug design. Once implemented and tested these techniques will be used on in-house active projects, assessing their performance and utility in guiding the development of new medicines. For example, measuring their value in trying to improve compounds binding affinity and ADMET properties. Therefore, the postdoctoral scientist will provide computational support to the chemistry team to address several drug design issues. This work will also provide the opportunity to combine AI-based to physics-based methods such as free energy perturbations (FEP) already in use in our structure-based drug design setting. The data scientist will also have the opportunity to gain hands-on experience of using these structure-based techniques and will benefit from Nvidia Tesla K80 GPU-equipped hardware for high-end scientific computing and data analytics.


Throughout the programme you will work directly with our CRUK drug discovery experts with the advantage of working in an integrated drug discovery programme, developing technical skills and industry-standard drug discovery knowledge, and also interpersonal skills that will enhance future employment opportunities.

Responsibilities:

  • Design and implementation of deep learning architectures for drug design applications
  • Train deep neural nets to understand and predict outcomes from in house and open molecular datasets (e.g. ChEMBL)
  • Build state-of-the-art generative models (GANs, VAEs, RNNs+RL, etc.) to design new chemical entities with specified activity profiles
  • Applying developed generative/predictive models to active oncology projects
  • Interact closely with experimentalists who will validate predictions

Essential qualifications and capabilities:

  • PhD in a relevant field
  • Programming experience with Python
  • Expert/Working knowledge of Keras, Tensorflow or similar ML frameworks
  • Excellent communication skills in both written and spoken English

Desirable skills:

  • Basic knowledge of chemistry
  • Basic knowledge of cheminformatics and medicinal chemistry concepts
  • Familiar with the application of machine learning to drug discovery projects
  • Experience with DeepChem, Knime, RDkit, Pipeline Pilot

This is a fantastic opportunity to work within the AI applied to drug discovery/design field joining a world-leading cancer research organization with the goal of improving human health. In return, we offer an inspiring, supportive and multi-disciplinary environment in a state-of-the-art, purpose built laboratory in which to further enhance your skills and knowledge of structural sciences, biophysics, cancer biology and drug discovery, providing you with the opportunity to make a real difference to the lives of cancer patients.


Informal enquiries are welcome and should be addressed to Dr Justin Bower; j.bower@beatson.gla.ac.uk (Joint Head of Beatson Drug Discovery Unit)

Closing date for applications is August 16th, 2019.

At the Cancer Research UK Beatson Institute, we are committed to increasing the number of female scientists at this level and strongly encourage female applicants to apply. We have recently introduced a highly attractive, innovative maternity policy, which includes providing a postdoc with support and funding so that their projects can continue during their maternity leave.

 

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