Senior Protein Scientist​/Antibody Engineer

At Lab Genius Therapeutics ("Lab Genius"), our mission is to discover the next generation of therapeutic antibodies by combining human and machine intelligence. We have pioneered the development of EVA™, a state‑of‑the‑art automated platform that enables closed‑loop discovery of high‑performing, non‑intuitive antibody designs using proprietary, ML‑grade datasets. For our wholly‑owned therapeutic pipeline, we are using this engine to establish a pipeline of highly selective T‑cell engagers and ADCs for the treatment of solid tumours.

Lab Genius has raised >£55M and is backed by top‑tier investors, including M Ventures, Octopus Ventures, LG Corp, Atomico, Kindred Capital, Lux Capital and Obvious Ventures among others. The company is headquartered in London (UK) where we have established a cutting‑edge antibody engineering facility. The team has more than 50 scientists and engineers.

You’ll be a pivotal member of the wet‑lab team, serving as the technical lead for antibody binding characterization. This is a high‑impact opportunity for a kinetics expert to not only execute assays but to build a world‑class antibody binding platform from the ground up. Your primary mission is to ensure that our ML models are fed with high‑resolution, high‑quality kinetic data.

You will design workflows using SPR (Surface Plasmon Resonance) and BLI (Biolayer Interferometry) to transition our discovery pipeline from crude screening to clinical‑grade lead optimization. You will also stress‑test binders for biophysical liabilities such as aggregation, instability, or poor solubility early in the pipeline.

• Design, implement, and own our internal antibody binding platform, selecting the best‑fit instrumentation (e.g., Biacore, Octet) to scale characterization capabilities.
• Lead high‑resolution kinetic screening campaigns to determine kon, koff, and KD for large panels of antibody candidates.
• Execute complex epitope binning and mapping studies to ensure diverse target coverage and support intellectual property filings.
• Partner with the Lab Automation team to integrate liquid handling with BLI workflows, moving toward fully autonomous binding assays.
• Work closely with our Data Science team to translate raw sensorgrams into clean datasets for ML/AI predictive models, ensuring our in silico scoring is grounded in precise physical measurements.
• Design and implement automated biophysical screening assays (e.g., HT‑protein stability, solubility, and self‑association) using 96‑ and 384‑well formats.
• Analyze data from high‑throughput screening and work with our data science team to feed biophysical “wet‑lab” data into predictive models (ML/AI) for in silico develop ability scoring.
• QC analyze, interpret and troubleshoot develop ability experiments working closely with other R&D teams.
• Conduct research in a self‑directed manner, troubleshooting complex binding profiles (e.g., multi‑phasic binding or non‑specific interactions) to provide actionable insights to the engineering team.
• Keep excellent experimental and data records for cross‑functional teamwork and project learnings.
• Organize and manage your time effectively, balancing competing priorities based on business goals and the focus of your wider team to deliver to timelines where others rely on you.

• PhD in protein/antibody engineering, protein biochemistry, or MSc with 3‑5 years of industrial experience in protein characterization a distinct advantage.
• Deep, hands‑on mastery of SPR (Biacore/Sierra) or BLI (Oct, sensor chip selection, immobilization strategies, and regeneration optimization.
• Proven track record of managing large‑scale screening campaigns (hundreds of samples per week) without compromising data integrity.
• Proficiency in data analysis software (e.g., Insight Evaluation, Scrubber) and a sophisticated understanding of 1:1 binding models vs. complex interactions.
• Experience in thermostability assays (DSF), ELISA‑based techniques, dynamic light scattering (DLS), and analytical UPLC techniques (SE‑HPLC, HIC‑HPLC).
• Deep understanding of antibody structure‑function relationships and PTM liabilities.
• Ability to generate and implement new…