Senior Scientist/Associate Principal Scientist, AI

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.

Date Posted

17-8月-2026

Closing Date

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.