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. The role involves advancing de novo design technologies to generate molecules for testing biological hypotheses at scale, building data to predict perturbation effects, accelerating validation of disease intervention points, and driving therapeutic discovery campaigns within the Data, Automation, and Predictive Sciences (DAPS) department. You will be the predictive engine for R&D, researching and embedding new methods to enable automation of the Design-Make-Test-Analyze cycle and driving Lab-in-an-Automated-Loop frameworks from target discovery to the clinic. You will work in close partnership across GSK to foster a collaborative, high-performing 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 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

• Required: 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, etc.) and output (imaging, omics, etc.) ML models
• Required: Experience to work as 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

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
• Demonstrated learning agility and scientific curiosity while driving impact amidst uncertainty
• Ability to generate conclusion reports, present data in team meetings, and participate in writing abstracts and publications

Education

• PhD or equivalent in a relevant field (as listed in Qualifications)

Additional Requirements

• No additional travel or physical demands are specified as essential in this description.