Senior Principal Scientist, Biologics AI Innovation

Responsibilities

Lead the development and application of advanced AI/ML models for the design, engineering, and optimization of biologics (e.g., monoclonal antibodies, proteins, nanobodies, multispecifics).

Collaborate with multidisciplinary teams to innovate and automate workflows, integrating experimental and computational platforms.

Mentor and guide junior data scientists, bioinformaticians, and molecular engineers in the application of data-driven approaches.

Evaluate emerging technologies and external partnerships relevant to AI-enabled Biologics Engineering.

Lead or contribute to the publication of high-impact scientific articles and present at internal and external conferences.

Establish best practices for integrating large, complex biological datasets (protein sequences, structures, biophysical data) into model development pipelines.

Translate scientific advances into actionable strategies for Biologics program teams, driving impact from hit discovery through candidate optimization.

Champion responsible innovation in AI, data privacy, and ethical use of machine learning in biologics research.

Qualifications

Ph.D. or equivalent in Computational Biology, Structural Biology, Bioinformatics, Computer Science, Engineering, or a related field.

Strong experience in biopharmaceutical RandD or academia, with a strong track record of innovation in AI or machine learning applications for biologics.

Deep expertise in protein modeling, biologics design, or related fields, with hands-on experience deploying deep learning or advanced statistical models in a research environment.

Proficiency with modern AI/ML tools and frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

Demonstrated experience working with large, complex biological and biophysical datasets.

Excellent communication, prioritisation, leadership, and cross-functional collaboration skills.

Strong publication record in peer-reviewed journals and demonstrated impact on biologics drug discovery programs.

Preferred Requirements

Experience leading teams or complex scientific projects in an industrial research setting.

Knowledge of structure-based drug design, antibody engineering, or protein-protein interaction modeling.

Familiarity with laboratory automation, high-throughput screening, and experimental design for biologics discovery.

Awareness of regulatory, ethical, and privacy considerations for data-driven drug ..... full job details .....