We have multiple exciting opportunities for computational chemists with skills and interest in applying AI generative and predictive models to drug discovery projects. We are looking for a highly motivated individuals who are passionate about applying AI and computational methods to solve multidimensional problems within drug design to progress the AstraZeneca Oncology project portfolio. We are recruiting at Senior Scientist or Associate Principal Scientist level, depending on experience., You will drive scientific discovery across multiple drug discovery projects and teams, with a focus on applying state-of-the art methods including structure- and ligand-based design, machine learning, cheminformatics workflows & artificial intelligence, to design molecules to accelerate the process of finding new drugs to treat cancer. You will work in an open and collaborative environment nurturing novel ideas alongside drug project teams. A major component of the role will be to apply generative AI methods to drug design and build predictive machine learning models for bioactivity and other properties. You will also produce cheminformatics workflows to accelerate computational drug design.
* A PhD (or equivalent experience) in Chemistry, Computational Chemistry/Cheminformatics or a related discipline., A strong knowledge of computational chemistry and/or cheminformatics and machine learning concepts.
* Interest in applying generative and predictive AI methods to medicinal chemistry problems in a drug discovery setting.
* Experience with multiple of the following: modelling protein structure and dynamics, structure- and ligand-based design, machine learning for property prediction, applying generative and predictive AI methods to projects.
* A good knowledge of physicochemical properties and DMPK and their importance in medicinal chemistry.
* Excellent communication, presentation, team working and influencing skills.
* Excellent time management abilities.
Desirable:
* Experience in using structure- and ligand- based computational methods in a drug discovery setting.
* Experience in applying generative and predictive AI methods to medicinal chemistry problems in a drug discovery setting, delivering tangible outcomes.
* Knowledge of a variety of machine/deep learning algorithms/architectures.
* Publications in computational chemistry or AI fields.
* Experience with scripting/programming (e.g. Python, R, C++, Java) and pipelining tools.
Are you ready to make a difference? Apply today!