Flexible start: Latest End of June, 2026. This is hybrid role with a minimum 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 focussed 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. This will enable them to increase food production, reduce land for agriculture and help mitigate climate change. In December 2021, Resurrect Bio was spun out of the top institute for molecular plant microbe interactions, The Sainsbury Lab, Norwich. Since then, we have attracted financial support from several renowned VCs, as well as UK Government grant funding. This role You’ll take ownership of the company’s AI-driven protein protein interaction tool, FloraFold®. The role will require: Fine-tuning, optimisation, and deployment of 3D protein structure predictions 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 us define our 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 your 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 use in 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). We will consider candidates with an MSc and 3 years of direct experience developing protein folding AI technologies. Application process This role uses blind recruitment practices to reduce unconscious bias in our hiring process. The system identifies information such as names, photos, and personal details that are removed during initial screening to ensure candidates are evaluated solely on their skills and experience. We are an equal opportunities employer committed to building a diverse and inclusive workplace. Applications are open on a rolling basis and may be closed at any time.