Protein Production Scientist, Biologics
Listed on 2026-07-16
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Research/Development
Biotech Research
The opportunity
Substrate is building the protein production cascade that turns a sequence into characterised, quality-controlled protein at scale, and you will build it from the first manual run. This is the work upstream of every protein data point Substrate generates: DNA design, molecular biology, protein expression, purification, and quality control, developed by hand and engineered to move onto automation.
The data this cascade produces is the product. Substrate is the critical infrastructure layer between AI and biology, and biological foundation models can predict but cannot experiment; the high-quality, large-scale data they need does not exist yet. Your work at the bench is what brings it into existence.
About SubstrateSubstrate is building the critical infrastructure layer between AI and biology: an AI-native automated lab that produces biological data for biology has a data problem, not a compute problem. Biological foundation models can predict but cannot experiment, and the high-quality, large-scale data they need does not exist. Substrate generates it, with quality and provenance built in. We are not a CRO and we are not a cloud lab.
The company was founded by four co-founders and is funded through a combination of equity and debt. The first lab is in London, with a larger automation node to follow. The work starts with two scientific verticals, protein characterisation and functional genomics, and this role sits at the centre of the protein work.
The roleYou will build the protein production cascade that sits upstream of molecular characterisation and functional assays: DNA design, molecular biology, protein expression, purification, and quality control through analytical characterisation. The cascade will eventually run autonomously on Substrate’s automation platform. In the first phase, you develop each step by hand, running protocols manually, setting reproducibility and quality thresholds, and proving each phase works before it moves onto instrumentation.
As the automation platform comes online, the work shifts toward instrumented execution, equivalence validation, and the engineering judgement calls that decide which manual steps get automated and which stay in human hands. You will work directly with the automation engineering and software teams on the boundary between scientific protocols and autonomous execution, at Scientist or Senior Scientist level, alongside Principal Scientists at the bench, and you will grow into protocol authorship over the first year.
Whatyou will do in your first twelve months Phase 0 – NOW to AUG 2026
Land in the lab. Set up your bench at the London site and start manual assay development alongside a senior member of the protein sciences vertical.
Get hands on the first priority protein production workflows as the day-one assay menu locks.
Start building DNA design and production (linear DNA), protein expression (cell-free), and protein purification and QC at high throughput. Run them by hand on equipment that will eventually move onto the automation platform, capturing the data-structure and metadata decisions that translate into automation design.
Build reproducibility, precision, and acceptance thresholds into the workflow.
Contribute to the day-one menu decisions and begin authoring SOPs for your slice of the assay portfolio. Help interview the scientists and lab technicians joining alongside you.
Have a linear DNA, cell‑free expression, purification, and QC workflow in a semi‑ automated state, running at the scale of hundreds to thousands per week and ready for full automation.
Co‑design protocols with the software and automation engineering teams so the manual versions you validate are automation‑ready by design. Decide which manual judgement calls have to be engineered out before they reach the platform.
Start building DNA design and production (plasmid DNA), protein expression (mammalian), and protein purification and QC at high throughput, again by hand on equipment that will move onto the platform.
Build reproducibility, precision, and acceptance thresholds into the workflow.
Contribute to co‑design conversations with…
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