Principal Scientist, Molecular Perturbation Modeling

Role Summary

As a (Senior) Principal Scientist in the Protein Design and Informatics (PDI) team, you will focus on translating biological mechanisms of disease to molecular mechanisms of therapeutics by integrating perturbation data to design new molecules that modulate disease phenotypes. You will be the predictive engine for R&D, focusing on researching and embedding new methods to enable automation of the entire Design-Make-Test-Analyze cycle, driving Lab-in-an-Automated-Loop frameworks from target discovery to the clinic - all stages of a therapeutic project. You will work in close partnership with many departments across GSK, fostering a high-performing team culture of collaboration, curiosity, consistency, agility, quality, peer review, and continuous improvement with a focus on creating medicines for patients.

Responsibilities

• Work to generate, validate, and integrate multimodal generative AIML models for the de novo design and multi-objective optimization of tool and therapeutic molecules (e.g., miniproteins, antibodies, antigens, peptides, ADCs, oligonucleotides).
• Guide molecular perturbation experiments that validate mechanisms of disease and show reversal of disease phenotypes and signatures.
• Build and exploit agent-orchestrated, integrated Design-Make-Test-Analyze cycles with automated experimental platforms, generating quality data at scale for project-specific and foundational models.
• Identify and advocate for opportunities in scientific computation and platform automation to drive therapeutic project plans with predictive technologies.
• Collaborate with external groups to further develop protein engineering computational methods.
• Predict and evaluate potential disease intervention points for their probability of success to be therapeutically modulated across any modality.

Qualifications

• PhD or equivalent in Bioinformatics, Physics, Chemistry, Computer Science, Structural Biology, or related fields
• Experience in protein structural or sequence analysis
• Experience in one or more programming languages (e.g., Python)
• Experience with training or applying multimodal input (sequence, structure, genetic, small/large molecular, etc.) and output (imaging, omics, etc.) ML models
• Experience to work as team lead or member; ability to work/lead effectively in a matrix environment
• Experience working across scientific and technical disciplines to deliver impactful solutions that drive project progression

Skills

• Experience developing or applying modern ML architectures for molecular design models (LLMs, diffusion models, flow-matching, Bayesian Optimization, GNNs, etc.)
• Experience with the design of multiple therapeutic modalities
• Experience designing de novo binders for specified targets and epitopes to answer biological questions
• Experience with cloud engineering production-ready robust and scalable scientific workflows
• Experience building and deploying agentic workflows
• Demonstrated learning agility and scientific curiosity while driving impact amid uncertainty
• Ability to generate conclusion reports, present data in team meetings, and contribute to abstracts and publications

Education

• PhD or equivalent in relevant field required