Substrate Bio
Molecular Characterisation Scientist, Biologics

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The opportunity
Substrate is building the molecular characterisation cascade that turns purified protein into trustworthy, quality-controlled, biophysically characterised data at scale, and you will build it from the first manual run. This is the work downstream of protein production and upstream of functional assays: quality control, binding, stability, and developability, 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 Substrate
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 heart of the protein characterisation work.
The role
You will build the molecular characterisation cascade that sits downstream of protein production and upstream of functional assays: the biophysical, analytical, and developability assays that decide what each molecule is and whether it holds up. The cascade will eventually run autonomously on Substrate’s automation platform. In the first phase, you develop each assay by hand, running protocols manually, setting reproducibility and quality thresholds, and proving each assay out 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. Every level works directly with the automation engineering and software teams on the boundary between scientific protocols and autonomous execution.
We are hiring across three levels:
- Principal Scientists own a slice of the assay menu end to end: scoping, designing the manual protocol, validating it to acceptance thresholds, authoring the SOPs that translate into automation design, and seeing it through to automated execution.
- Scientists work alongside Principal Scientists at the bench, executing the experiments, contributing to validation work, and growing into protocol authorship over the first year.
- Lab Technicians are the hands-on execution layer: following established SOPs, preparing reagents and consumables, maintaining equipment, and running routine steps of validated protocols so that Scientists and Principal Scientists can focus on design and troubleshooting.
What you 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 characterisation assays as the day-one menu locks. Start building QC (purity, concentration, oligomeric state), binding (SPR or BLI), and stability (nanoDSF, DLS) readouts. 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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Phase 1 – SEP to DEC 2026
- Develop and validate a QC (purity, concentration, oligomeric state), binding (SPR or BLI), and stability (nanoDSF, DLS) workflow, first manually and then in a semi-automated state, running at a scale of hundreds to a thousand samples per week and ready for full automation.
- Begin development of a developability package (HIC, heparin binding, AC-SINS, and similar), with assay design guided primarily by downstream automation compatibility.
- 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.
- Contribute to co-design conversations with the first commercial customers, including the foundation-model partners coming online from 2027.
Phase 2 – JAN to MAR 2027
- Workcells arrive in the lab. Move the validated assays onto them, running with instrumentation and human intervention in the loop. Validate equivalence against your manual baselines and triage failures.
- Open the assay menu to customers through manual and semi-automated services. Run real experiments for real customers.
- Help bring on the next scientists and lab technicians as the vertical grows.
Who you are
You are a protein scientist who is excited about the actual work: designing, validating, and running biophysical and developability assays at the bench. You are comfortable in the details.
You have hands-on experience collecting and analysing binding kinetics and affinity data, and assessing the developability of biologics. 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.
We are hiring across three tiers: Lab Technician, Scientist, and Principal Scientist. The work is hands-on bench science at all levels, with collaboration into automation and software; the difference is depth of ownership, design authority, and responsibility. We do not hire people into boxes, and the early team stretches beyond the strict edges of any role.
Must Have – All Three Tiers
- Hands-on experience with biophysical and/or analytical instrumentation for protein characterisation.
- Comfortable executing assays in a high-throughput format through manual, semi-automated, and instrumented phases.
- A track record of working alongside non-scientist colleagues (automation, software, computational) on a shared workflow.


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Must Have – Lab Technician
- Relevant hands-on lab experience, including apprenticeships or technician roles, is the primary consideration.
- Comfortable following written SOPs precisely and flagging deviations. You do not need to design experiments, but you do need to execute them reliably and communicate clearly when something looks off.
- Hands-on familiarity with basic wet-lab technique: accurate pipetting, buffer and reagent preparation, sample handling, plate setup, and instrument use. Exposure to plate readers, chromatography systems (HPLC), biophysical instruments (nanoDSF, DLS, SPR/BLI), or semi-automated workflows (plate-based liquid handlers) is helpful but not required.
- Comfortable in a fast-paced, early-stage environment where protocols are still being written. You are methodical, safety-conscious, and do not take shortcuts.
- Aware of structured experimental data capture, and able to use a LIMS, ELN, or analogous infrastructure.
Must Have – Scientist
- A PhD in protein biophysics, analytical characterisation, or biologics developability, with two or more years of relevant hands-on experience; or an MSc with five years of experience in the same area.
- Independent, hands-on competence on at least one biophysical binding platform (SPR or BLI), plus one or more orthogonal characterisation or developability assays (for example nanoDSF/DSF, DLS, analytical SEC, HIC, AC-SINS, cIEF, or PAIA).
- Some exposure to one or more of these areas at high throughput (96 and 384-well plate formats).
- Confident data analysis: kinetics fitting and interpretation, and telling instrument artefacts apart from genuine molecule behaviour.
- Fluency with structured experimental data capture, and proficiency with a LIMS, ELN, or analogous infrastructure.
- Ready to grow into protocol authorship and SOP ownership over the first twelve months.
Must Have – Principal Scientist
- A PhD in protein biochemistry, biophysics, analytical characterisation, or biologics developability, with five or more years of relevant hands-on experience (at least two in industry); or a relevant science MSc with eight years of equivalent bench experience in protein science (at least two in industry).
- Independent, extensive experience with biologics characterisation workflows across at least three core areas, such as full SPR/BLI kinetics, epitope binning, immunoassay (ELISA)-based assays, thermal and colloidal stability characterisation (nanoDSF, DLS, SLS, analytical SEC), and developability assessment (HIC, heparin LC, AC-SINS, forced degradation).
- Experience in two or more of these areas at high throughput (96 and 384-well plate formats), establishing and optimising workflows, SOPs, and validation.
- Proficiency with structured experimental data capture using a LIMS, ELN, or analogous infrastructure.
- 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.
Nice to Have
- Direct
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