Computational Biologics Design

Typical Accountabilities

• Lead the in silico support on pipeline therapeutic projects in collaboration with AZ stakeholders
• Work collaboratively with data and drug discovery scientists to establish structural analytics workflows for biologics discovery
• Contribute to the development of an end-to-end data analysis capability within Biologics Engineering team as part of a cross-functional team
• Drive innovative structural, generative & machine learning methods for the design and optimisation of biologic therapeutics
• Participate in strategic external collaborations
• Demonstrate effective communication to translate complex concepts to non-experts in internal and external scientific meetings

Must Have

• PhD in relevant field (e.g. Structural Biology, Computer Science, Bioinformatics, Physics and Mathematics)
• 2 years experience in Silico Design
• Knowledge of computational structural biology and demonstrated application of data analysis methods
• Experience with structural modelling platforms (e.g. Schrodinger, Rosetta etc)
• Familiarity with antibody discovery & optimisation, protein structures
• Skilled in applying generative AI, Machine learning or deep learning to design and optimise proteins
• Strong, professional communication skills and excellent attention to detail, capable of developing good working relationships with diverse individuals
• Experience working within a team environment
• Acts with integrity and does the right thing

Desirable

• Knowledge of FAIR data principles
• Experience with the analysis of large structural, sequence and experimental datasets