Protein Production Scientist, Biologics
Role Summary
Join Substrate Bio as a Protein Production Scientist to develop and automate protein production processes in a cutting-edge lab environment in London.
About the Organisation
Substrate is building the critical infrastructure layer between AI and biology: an AI-native automated lab that produces biological data at scale. AI 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.
Most protein science roles like this inherit an established workflow and optimise it. This one. does not. No assay in this vertical is being retrofitted onto automation; every protocol is designed for AI-in-the-loop execution from the first manual run. The data each assay produces, its output structure, metadata, provenance, and consistency across runs, is treated as a first-class scientific constraint, because that data feeds directly into foundation-model training pipelines. Your decisions at the bench affect what the orchestrator has to do and what data leaves the building.
Some scientists find this energising; others find it outside the lane they trained for. It is worth knowing in advance which one you are.
Minimum Requirements
This role is open at Scientist and Senior Scientist level. The work is hands-on bench science at both, with collaboration into automation and software; the difference is depth of ownership, design authority, and how much of the team you help build. We do not hire people into boxes, and the early team stretches beyond the strict edges of any role.
- You are a protein scientist who is excited about the actual work: designing, running, andvalidating at the bench.
- You are comfortable in the details. You have hands-on experience with high throughput, plate-based methods across molecular biology, protein expression, purification, and QC.
- The shape of the problem is what attracts you: assays designed for autonomous execution from day one, in a business where the data the lab produces is itself the product.
- You write good SOPs, and you hold yourself and your colleagues to clear reproducibility thresholds. You are pragmatic about being hands-on in the early phase, when the cadence is heaviest, and you understand it eases as protocols move onto instrumentation.
- You enjoy working at the boundary with non-biologist colleagues (automation engineers, software engineers, AI researchers), and you do not require them to be scientifically fluent before you will collaborate.
- Comfortable handling DNA design and linear and plasmid DNA production at high throughput, expressing proteins, and purifying them with QC steps for validation, executing protocols at the bench through manual, semi-automated, and instrumented phases.
- Core experience within biologics.
- A track record of working alongside non-scientist colleagues (automation, software, computational) on a shared workflow.
- A PhD in protein biochemistry, molecular or structural biology, biophysics, analytical characterisation, or biologics developability, with two or more years of relevant hands-on experience; or a relevant science MSc with five or more years of equivalent bench experience in protein science.
- Independent, hands-on competence across protein science: molecular biology (DNA production with Gibson and Golden Gate assembly at transfection-grade quality), protein expression (cell-free, IVTT, E. coli and mammalian), and protein purification (automated magnetic-bead workflows), with exposure to at least one of these at high throughput (24, 96, and 384-well plate formats). Protein characterisation across at least two core biophysical methods (for example CE-SDS, DLS, nanoDSF/DSF, analytical SEC, HIC, or LC-MS intact mass analysis).
- Confident data analysis, including telling instrument artefacts apart from genuine molecule behaviour.
- Fluency with structured experimental data capture, and proficiency with a LIMS, ELN, or analogous data infrastructure.
- Ready to grow into protocol authorship and SOP ownership over the first twelve months.
- Direct experience moving biophysical or analytical assays from manual workflows onto lab automation platforms (at least a handoff into an automated platform).
- High throughput experience in at least one core biophysical platform (SPR or BLI for binding kinetics), plus one or more orthogonal characterisation or developability assays (for example nanoDSF/DSF, DLS, analytical SEC, HIC, AC-SINS, cIEF, or CE-SDS).
- Experience developing novel high throughput technologies in DNA generation, cell expression (cell-free, mammalian), or bead-based purification.
- Method development and validation experience: defining acceptance criteria, references, and controls that other scientists have run successfully.
- SOP and protocol authorship that others have executed, and experience supervising at least one junior scientist or technician.
- Experience working with computational or AI/ML colleagues on closed-loop assay programmes.
- Background at an AI-native biotech or foundation-model company.
Eligibility Criteria
Eligible candidates should have experience in molecular biology, protein expression, and purification processes.
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