About this job

As world leaders in antibody drug discovery and development, our client offers a unique opportunity to use cutting edge technologies to help shape the delivery of the next-generation antibody therapeutics.

Using your expertise in computational biology, you will join the Antibody Discovery team to develop, validate and employ computational methodologies for the discovery of monoclonal antibody-based therapeutics. You will be working closely with wet lab, computer-aided drug-design and data sciences teams to drive this innovative project forward.

Other key responsibilities:

• Develop workflows for antibody cognate pairing analysis/in silico interpretation of antibody repertoires
• Explore and define how the combination of machine learning and computational methods can be applied to antibody-antigen binding interactions
• Workflow/algorithm development and testing using commercial, open source or internally developed computational tools
• Present strategy and data at cross functional meetings
• Keep up to date with new technologies to continuously improve antibody discovery efficiencies

The ideal candidate will have:

• A PhD in computational sciences (or equivalent)
• Experience of Python coding and ML methodologies
• Exceptional organisation, communication and inter-personal skills
• Ability to deliver to tight deadlines and work within multi-disciplinary teams
• Desirable knowledge of biological domains e.g. antibody biology and practical applications of in silico analyses from antibody data
• Desirable experience of docker/cloud platforms

This is an exciting opportunity for a bright and enthusiastic scientist to join this company’s prestigious 18 month Postdoctoral research programme. If you believe you are a good fit, apply with VRS today!

Keywords: antibody discovery, antibody drug discovery, computational biology, machine learning, ML, Python, data science, anti-body based therapeutics, in silico, computational methods, algorithm development, bioinformatics, Berkshire, Reading, South East England, VRS8264GG

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