Join AstraZeneca's Oncology R&D in our Beijing R&D Center as a Machine Learning and AI Specialist and help shape the future of drug discovery. At AstraZeneca, we are building a variety of AI powered tools to accelerate the drug discovery process. In this role you will be responsible for implementing AI architectures for prediction of properties and 3D structures of small and large molecules complexes. Together with your colleagues you will create enhanced data sets for retraining and focusing these methods for specific use cases. You will benchmark different methods and build optimal pipelines for delivering accurate and impactful predictions. You will operate in a collaborative environment with other specialists in China and globally within R&D, and you'll be encouraged to publish and present your work at leading conferences.
You will:
About AstraZeneca
AstraZeneca is a global, science-led biopharmaceutical company committed to transforming patients' lives through innovative medicines. In Oncology R&D, we combine deep biological insight with state-of-the-art AI to accelerate molecular design and decision-making. Our teams operate in an open, collaborative environment across Beijing (China), Cambridge (UK) and Boston (USA), sharing best practice and pushing the boundaries of computational chemistry and machine learning. By joining us as a Senior Scientist, you will contribute to a vibrant community of scientists pioneering computer-aided drug design – and have the platform to publish, present, and shape the next wave of innovation.
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
Tagged as: Life Sciences
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