Associate Principal Scientist – Biologics AI Innovation

Role Summary

Associate Principal Scientist – Biologics AI Innovation. Drive Biologics AI innovation at AstraZeneca’s US R&D centers in Waltham, MA or Gaithersburg, MD. Integrate artificial intelligence with wet-lab discovery to enable synergistic advances in biologics engineering. Collaborate across computational and experimental functions and translate high-quality data for next-generation biotherapeutics.

Responsibilities

• Lead and design AI strategies for biologics discovery and engineering, focusing on AI‚Äìwet lab integration and translation of computational findings to experiments.
• Oversee development of innovative models, including protein language models, structure prediction models, de novo protein design, and multi-modal approaches combining sequence, structure, and biological activity data.
• Act as a scientific bridge and champion cross-functional collaboration between AI scientists and wet-lab teams within the US, aligned with global teams.
• Drive generation, curation, and utilization of high-quality wet-lab data; provide actionable feedback to experimental teams to optimize data production for ML applications.
• Evaluate, recommend, and implement emerging technologies, adopting best practices in data science, computational biology, and protein engineering to ensure innovation and delivery.
• Mentor junior scientists and provide scientific leadership in biologics AI, fostering a collaborative, innovative, and high-performing team environment.
• Communicate progress, challenges, and strategy to stakeholders at all levels, contributing to strategic decision-making and representing the team in collaborations.
• Author scientific publications, contribute to intellectual property, and represent AstraZeneca in the external scientific community through presentations and collaborations.

Qualifications

• Required: Master with 2+ years of experience or PhD with 0+ years in mathematics, physics, computer science, statistics, bioinformatics, or related discipline, with substantial AI/ML experience in biological problems.
• Deep expertise and hands-on track record in developing and deploying ML/DL models for protein sequence and structure analysis, biologics design, or related fields.
• Experience leading initiatives that combine computational modeling with experimental biology, ideally in therapeutics or biopharmaceutical settings.
• Strong programming and analytical skills, including Python and AI/ML frameworks (TensorFlow, PyTorch, or JAX).
• Familiarity with large-scale data engineering, cloud computing, and FAIR data principles.
• Excellent communication and leadership skills, with proven success in cross-functional and multi-site collaborations.
• Demonstrable record of scientific innovation evidenced by publications, patents, or successful projects in biologics discovery/engineering.

Preferred Qualifications

• Experience with structural informatics, structural biology, or structure-based rational design.
• Experience with molecular dynamics simulation and structure modeling.
• Experience with multi-modal learning, agentic AI, or integration of heterogeneous biological data formats.
• Prior leadership, mentoring, or line management experience in industrial or academic R&D.
• Recognized presence in the external scientific community through publications, conference presentations, or collaborations.

Skills

• AI/ML for biology; computational biology; protein engineering
• Cross-functional collaboration; scientific communication; data-driven decision making
• Data curation, management, and quality control for ML applications
• Protein structure and sequence analysis; de novo design

Education

• Master‚Äôs degree with 2+ years of relevant experience or PhD with relevant experience in a related discipline