Senior Scientist – Biologics AI Innovation Full-time NEW

Senior Scientist

We are seeking an experienced and visionary Senior Scientist to drive Biologics AI innovation at AstraZeneca's US R&D centers in Waltham, MA or Gaithersburg, MD. This pivotal leadership role will focus on integrating state-of-the-art artificial intelligence with wet-lab discovery, enabling synergistic advances in biologics engineering. You will work collaboratively across computational and experimental functions, influence the direction of AI-driven research, and champion the seamless collection and translation of high-quality data for the design of next-generation biotherapeutics.

Key Responsibilities

As a Senior Scientist, your main responsibilities will be:

• Lead and design AI strategies for biologics discovery and engineering, with a focus on AI–wet lab integration and accelerated translation of computational findings to experiments.
• Oversee and guide the 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 for cross-functional collaboration between AI scientists and wet-lab teams within the US, and in close alignment with global teams.
• Drive the generation, curation, and utilization of high-quality wet-lab data; provide actionable feedback to experimental teams for optimizing data production for ML applications.
• Evaluate, recommend, and implement emerging technologies, adopting best practices in data science, computational biology, and protein engineering to ensure world-class 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 internal and external collaborations.
• Author scientific publications, contribute to intellectual property, and serve as an ambassador for AstraZeneca in the external scientific community through presentations and collaborations.

Required Qualifications

• Master and 2+ years experience or Phd and 0+ years of experience in mathematics, physics, computer science, statistics, bioinformatic, or a related discipline, with substantial academic or industry experience in the application of AI/ML to biological problems.
• Deep expertise and hands-on track record in developing and deploying machine learning and deep learning models for protein sequence and structure analysis, biologics design, or related fields.
• Demonstrated experience in leading initiatives that combine computational modeling with experimental biology, ideally in a therapeutics or biopharmaceutical setting.
• Strong programming and analytical skills, including proficiency with Python and major AI/ML frameworks such as TensorFlow, PyTorch, or JAX.
• Familiarity with large-scale data engineering, cloud computing, and FAIR data principles.

Preferred Qualifications

• Experience with structural informatics, structural biology, or structure-based rational design.
• Experience with molecular dynamic simulation and structure modeling.
• Experience with multi-modal learning, agentic AI, or the 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.

Why Join Us?

As part of AstraZeneca's dynamic US biologics R&D community, you will play a critical role in shaping the future of AI-driven biologics discovery and engineering. Collaborating across cutting-edge computational and experimental teams, you'll drive innovation that brings transformative medicines to patients around the world. You will be supported by a collaborative, inclusive, and empowering environment, with unparalleled opportunities for scientific impact and personal growth.