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, researching and embedding new methods to enable automation of the Design-Make-Test-Analyze cycle, driving Lab-in-an-Automated-Loop frameworks from target discovery to the clinic at all stages of a therapeutic project. You will collaborate across GSK to foster a high-performing team culture focused on creating medicines for patients.

Responsibilities

• Generate, validate, and integrate multimodal generative AIML models for 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 disease mechanisms and demonstrate reversal of disease phenotypes and signatures.
• Build and exploit agent-orchestrated, integrated Design-Make-Test-Analyze cycles with automated experimental platforms, producing high-quality data at scale for models.
• Identify opportunities in scientific computation and platform automation to drive therapeutic project plans with predictive technologies.
• Collaborate with external groups to develop protein engineering computational methods.
• Predict and evaluate potential disease intervention points for their probability of therapeutic modulation across modalities.

Qualifications

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

Skills

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

Education

• PhD or equivalent degree as specified in Qualifications.