Key Responsibilities

As an AI Scientist/Senior Scientist, you will:

• Design, develop, benchmark, and implement advanced AI/ML models (self-supervised and supervised) for biologics discovery and engineering, including protein language models, structure prediction models, de novo design algorithms, and multi-modal approaches that integrate sequence, structure, biological, biochemical, biophysical, and functional data.
• Collaborate closely with wet lab scientists (primarily based in the UK and US) to guide experimental design, ensure the generation of high-quality, relevant datasets, and curate and manage wet lab data for modeling purposes.
• Analyze and interpret complex biological data, integrating machine learning with domain knowledge in protein science, biochemistry, biophysics, structural biology, and therapeutics development.
• Keep abreast of the latest developments in AI, computational biology, and biologics engineering; proactively identify and evaluate innovative technologies and methodologies relevant to biologics R&D.
• Effectively communicate complex technical concepts and results to multidisciplinary teams and stakeholders, bridging the gap between computational and experimental domains.
• Contribute to high-impact scientific publications, patent filings, and strategic collaborations both internally and externally.
• Collaborate cross-functionally in developing agentic AI solutions to address critical questions related to biologics engineering.
• Identifying and building local partnership opportunities (academic or industry) to accelerate impact in AI-driven biologics discovery

Required Qualifications

• Master or equivalent experience in mathematics, physics, computer science, computational biology, bioinformatics, or a related discipline.
• Hands-on experience in developing and applying machine learning/deep learning models, preferably for biological sequences (proteins, antibodies, peptides) or structures, in both self-supervised and supervised ways.
• Demonstrated programming proficiency in Python (and relevant ML/AI frameworks such as TensorFlow, PyTorch, JAX).
• Experience with multi-modal machine learning or integrating heterogeneous data types (such as sequence, structure, functional data).
• Experience in handling, curating, and analyzing large-scale biological datasets.
• Ability to work collaboratively in a fast-paced, multidisciplinary, and cross-geographical research environment.
• Clear and effective communication skills, with fluency in English.

Preferred Qualifications

• Knowledge of state-of-the-art approaches in protein modeling, structure prediction, or de novo design.
• Experience and expertise in agentic AI development
• Familiarity with large-scale cloud computing and modern data engineering practices.
• Publication record in top-tier AI, computational biology, or protein engineering journals/conferences.
• Understanding of biologics drug discovery.

Why Join Us?

At AstraZeneca’s Beijing R&D Center, you will be at the forefront of AI-driven biologics innovation. You’ll have the opportunity to work with leading experts across biology and data science, leverage state-of-the-art technologies, and make a tangible impact on the next generation of biologic medicines. We offer a collaborative, inclusive, and scientifically inspiring environment, with strong support for your professional growth.