AI Research Scientist | Protein-Protein Interactions

Flexible start: Latest End of June, 2026. Salary: £70-100k salary based on experience + Bonus. This is a hybrid role with a minimum of 3 days in the lab at White City, London (W12 7RZ) required.

About Resurrect Bio

Resurrect Bio is a VC-backed plant biotech start-up, discovering how to make crops resistant to disease using gene editing. We fix the immune system of crop species. We have a unique pipeline and platform for discovering resistance genes in crops which have been defeated by pathogens and pests. We then resurrect (restore) those resistance genes to make the crop resistant again, without introducing any new DNA to the crop. We’re focused on delivering for the world’s farmers a better way to protect their plants, using the crop's own immune system instead of spraying chemicals, enabling them to increase food production, reduce land for agriculture and help mitigate climate change.

This role

You’ll take ownership of the company’s AI-driven protein-protein interaction tool, FloraFold®.

• Fine-tuning, optimisation, and deployment of 3D protein structure prediction models
• Integrating experimental data to improve structure-based functional inference
• Optimise GPU/Cloud workflows for large-scale model fine-tuning and high-throughput structure prediction
• Working closely with experimental biologists to validate model predictions in the lab
• Investigate and implement novel training strategies and protein interaction scoring capabilities

This is a hands-on role suited to someone very comfortable writing code, training models, and helping define the product roadmap. The computational team is integral to Resurrect Bio and is small but growing. The role can be hybrid or based at our lab in White City, London.

What we offer

• £70-100k salary based on experience
• Share options in Resurrect Bio
• 10% annual bonus on base salary when the company hits milestones
• 34 days of annual leave, including bank holidays
• Pension plan
• Private medical insurance
• 35 hours per week, Monday-Friday

Required skills

• Experience with deep learning model training, fine-tuning, and evaluation for protein folding predictions
• Proficiency in Python and libraries used in AI applications (e.g. PyTorch, JAX, Tensorflow)
• Strong data analysis and engineering capabilities, including working with large-scale biological datasets and building robust data pipelines
• Understanding of protein structure, folding, and sequence-structure relationships
• Ability to translate computational predictions into biological insights
• Excellent communication skills with ability to present complex research findings to both technical and non-technical audiences

Nice to have

• Experience with protein language models
• Experience with workflow management tools like Nextflow
• Familiarity with HPC/Cloud computing (we use GCP)

Qualifications/Experience

A PhD in a directly relevant discipline (e.g., Computational Biology, Machine Learning, Bioinformatics with a strong emphasis on protein engineering). Candidates with an MSc and 3+ years of direct experience developing protein folding AI technologies will also be considered.

Application process

This role uses blind recruitment practices to reduce unconscious bias. The system removes personal details during the initial screening so that candidates are evaluated solely on skills and experience. We are an equal-opportunity employer committed to building a diverse and inclusive workplace. Applications are open on a rolling basis and may be closed at any time.