Computational Biologist (AI)

Location: London, UK; remote working available with access to the London office

Company

hirify.global is a public benefit company building open AI-powered molecular modelling tools for programmable biology and drug discovery.

What you will do

• Apply hirify.global models to antibody, peptide, and protein therapeutic design problems for internal research and external drug discovery programs.
• Build end-to-end protein design and optimisation pipelines combining generation, structure prediction, sequence design, scoring, developability, and candidate selection.
• Analyse large-scale natural, generated, and experimentally tested protein sequence and structural data using similarity analysis, clustering, alignment, interface analysis, and diversity selection.
• Build evaluation datasets and identify where protein design models succeed or fail.
• Connect experimental measurements such as binding, affinity, expression, stability, and developability to computational predictions and design decisions.
• Work with clients, scientific partners, Research, and ML teams to interpret results and improve models, ranking methods, and design workflows.

Requirements

• MSc, PhD, or equivalent experience in computational protein engineering or a related field.
• Strong programming skills, particularly in Python, with experience building scientific software, data pipelines, and analysis tooling.
• Hands-on experience with protein design, protein optimisation, or protein modelling tools and an understanding of their assumptions, outputs, and limitations.
• Advanced experience analysing large collections of protein sequences and structures, including clustering, similarity analysis, diversity selection, and visualisation.
• Ability to analyse experimental results and connect binding, affinity, expression, stability, and developability outcomes to computational predictions.
• Experience with modern protein design and modelling methods such as ProteinMPNN, RFdiffusion, hirify.globalGen, hirify.global, BindCraft, or related tools, plus strong communication skills.

Nice to have

• Understanding of SPR, BLI, ELISA, FACS, and other methods for characterising protein interactions.
• Experience analysing large-scale protein design campaigns involving thousands to millions of generated sequences or structures.
• Experience working with biotechnology or pharmaceutical partners and translating drug discovery objectives into computational workflows.
• Open-source scientific software contributions or publications in protein design, computational biology, structural biology, protein engineering, or biomolecular machine learning.

Culture & Benefits

• Flexible remote working and access to the London office.
• Opportunity to work on AI for biology alongside researchers in machine learning and molecular modelling.
• Direct impact on scientific discoveries and drug discovery programs.
• Competitive compensation and significant equity.