Director, Head of Computational Design

Overview

The Director, Head of Computational Design is accountable for the design and application of new advanced computational methods, including Large Language Models (LLMs) and AI, for cutting-edge mRNA design and next-generation vaccine and platform design and development.

This role guides the design and optimization of nucleic acid therapeutics (e.g., mRNA), associated vaccine platforms (e.g., vaccines, antigens, multiple antigens presenting systems, and adjuvants) and delivery systems (LNPs).

Providing innovative in silico solutions — encompassing structural bioinformatics, molecular modeling, and AI/ML-driven design — this role integrates active learning into Discovery Technology workflows to enhance immunogenicity, efficacy, and stability. This role supports discovery and preclinical research, translational, and early clinical stages as requested by DPLs, VDLs, PILs, and clinical sciences teams.

The Head leads and mentors a world-class team, ensuring scientific excellence, strategic alignment with the Head of VIDRU Data Sciences and VIDRU R&D project/platform leaders, and adherence to top scientific and industry standards for all deliverables.

• Provides strategic vision and leadership for computational molecular design initiatives within VIDRU Data Sciences, with a primary focus on next generation mRNA design, vaccine, antigen and NLP platform development.
• Leads and manages a multidisciplinary team of computational design scientists, fostering a culture of high performance, scientific innovation, and continuous professional development.
• Directs the development and application of advanced computational design methodologies, including structural bioinformatics, molecular modeling, and protein/nucleic acid engineering, with a strong emphasis on mRNA sequence and structure optimization.
• Drives the leveraging of AI and LLMs for de novo design, optimization, and predictive modeling (e.g., molecular stability, protein expression, immunogenicity) of antigens, mRNA, LNPs, adjuvants, and monoclonal antibodies/ADCs.
• Ensures scientific integration by embedding computational design experts within discovery project teams, providing critical data science expertise from early-stage research through candidate selection and optimization, particularly for mRNA and platform-specific data.
• Integrates computational predictions with experimental validation via active learning loops, establishing strong links with Disco Tech laboratories to accelerate iterative molecule design and optimization cycles.
• Establishes strong collaborative links with DPLs, VDLs, PILs, TPLs and clinical sciences teams to ensure computational design insights directly inform and accelerate pipeline progression.
• Drives innovation in computational design analytics by partnering closely with GSK's AIML and R&D Tech divisions, and external academic/industry Key Opinion Leaders, exploring and integrating novel AI/ML methods and computational paradigms.

• PhD or equivalent experience. Computational Biology, Data Science, Mathematics and Physics, Biological or Chemical Engineering, Bioinformatics, Computational Life Sciences or equivalent.
• In depth theoretical background and practical experience on quantitative sciences applied to biology and strong competences in computer science.
• Research experience and publication record in one or more of the relevant areas of expertise.
• 8+ yrs in scientific experience, including four years of direct/matrix people management and international leadership responsibilities (e.g. principal investigator for international R&D projects in relevant areas).
• Proven capacity to use the theoretical background and education to solve actual problems of R&D projects working and leading teams in cross-functional setting. This role shall act as a global reference person for the function and perform people management and coaching of global staff.

• Demonstrated strong proficiency / publication record in one or more of the following areas:
• Advanced molecular modelling and simulation (e.g., molecular dynamics, docking, free energy calculations).
• Structural bioinformatics and protein…