---
title: 'Protein Production Scientist, Biologics at Substrate Bio'
canonical: 'https://feeny.ai/job/protein-production-scientist-biologics-substrate-bio-london-j9tks50dnee6'
type: 'job'
last_seen: '2026-10-14'
---

# Protein Production Scientist, Biologics at Substrate Bio

- **Company:** Substrate Bio
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-09
- **Last confirmed live:** 2026-10-14
- **Apply:** https://jobs.ashbyhq.com/substrate-bio/5c3e8846-d4a8-4892-8728-909880a8c044

## Job description

LEVEL: Scientist / Senior Scientist · LOCATION: London (20 Triton Street) · PATTERN: In-person, lab-based

The opportunity We are 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 we generates: DNA design, molecular biology, protein expression, purification, and quality control, developed by hand and engineered to move onto automation.

## About us

AI for biology has a data problem. The data that matters most doesn’t exist yet, so we’re building the infrastructure to produce it, with quality and traceability built in from day one. We’re in stealth and heads-down on execution. We’ll share more about what we’re building once you’ve spoken with the team.

## The role

You 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 our 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.

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 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.

## PHASE 1 · SEP TO DEC 2026

◆ 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 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, running, and validating 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. 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.

## MUST HAVE

◆ 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.

## NICE TO HAVE

◆ 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.

## Why this is unusual

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.

## How we work

This role is on site five days a week at our London Lab. The lab is a physical place and the work is in it. We work in the open. Decisions are written down, work happens in Slack rather than scattered across tools, and the week is bookended by a Monday kick-off and a Thursday wrap that the whole company attends. There is a quarterly offsite. Each person owns their area and makes the call inside it, and we will expect that of you early rather than late. UK benefits are 30 days of annual leave plus public holidays, a pension with a 10% employer contribution, and top-tier Bupa private health cover. More is added as the team grows.

The team you will join You will join the protein sciences vertical, working day to day alongside a senior member of the vertical and the automation engineering and software teams who turn the manual cascade into an automated one.

Our process and how to apply Our process has four stages. A short screening call about the role and the practicalities. A conversation about how you work, run from the same template for every candidate, before anything technical. A practical exercise drawn from a real problem in our lab, followed by a discussion of what you did and why. Then references, aimed at whatever we still want to understand. We are an equal opportunity employer. We make hiring decisions on merit, scope-fit, and the strength of the working relationship we expect to build with each hire. Applications welcome from candidates of any background.

## About Substrate Bio

## Company Overview
- **One-liner**: Substrate Bio is building a network of fully autonomous wet laboratories that produce the high-quality, structured data that foundation models in biology are bottlenecked on.
- **Entity Type**: Private (Pre-Seed stage, funded by a combination of venture funding and government grants)
- **Headquarters**: London, United Kingdom (King’s Cross)
- **Founded**: 2023 (Incorporated June 13, 2023)
- **Founders**: Mostafa ElSayed (CEO, also founder of Automata), Oli Hoy (formerly VP Customer Experience at Automata), Alexey Morgunov (AI Scientist co-founder), and a founding biology lead joining shortly.

## Core Business
- **Primary industry/industries**: Deep Tech, Biotech / Life Sciences, AI-driven biology, Lab Automation
- **Target customers**: B2B; foundation model labs, global pharmaceutical companies, and AI-driven biology researchers.
- **Mission or purpose statement**: To become the critical infrastructure layer for AI-driven biological discovery by building a network of autonomous wet labs that operate in a closed loop with foundation models.

## Products & Services
- **Autonomous Wet Lab Platform**: A network of fully autonomous wet laboratories (first node in King’s Cross, London) where pipetting robots run continuously, executing experiments end-to-end with no human intervention. The labs return structured data within hours.
- **Closed-Loop Integration with Foundation Models**: The platform is designed so that foundation models design the experiments and read the results in real time. Better data improves the models, and better models design better experiments.
- **Token-Based Usage Pricing**: Access to the platform is sold on a usage basis via a token-based model that maps physical inputs (instrument time, materials, compute, complexity) onto a cleaner customer-facing unit of value.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed (likely pre-seed/seed stage, funded by founders and undisclosed angels).
- **Key Metric**: Total Funding — Not publicly disclosed, but funded in parallel by venture funding and government grants (including ARIA and DSIT grants).
- **Notable Investors/Partners**: Not publicly named. The company is spinning out of Automata, the UK lab automation company.
- **Growth Signals**: Active hiring in 2026 (Head of Functional Genomics, Chemistry Principal Scientist, Financial Controller). Targeting a team of ~32 people by the end of Q1 2027. First lab node opening in King’s Cross, London, with several integrated workcells and two scientific verticals online by mid-2027.

## Competitive Advantages
- **Autonomous, Not a Cloud Lab or CRO**: Substrate is building a fully autonomous lab platform with closed-loop integration, differentiating itself from traditional cloud labs or contract research organizations (CROs).
- **Data Quality for AI**: The core thesis is that the bottleneck in AI-driven biology is high-quality, structured experimental data. Substrate’s automated labs are designed to produce this data at scale, creating a unique moat.
- **Open Access Model**: Researchers access the platform through an API with no minimum commitment and no exclusivity, lowering the barrier to entry for AI labs.
- **Deep Integration with Foundation Models**: The platform is built from the ground up to operate in a closed loop with AI models, not as an afterthought.

## Strategic Focus
- **Building the First Node**: The immediate priority is opening the first autonomous lab node in King’s Cross, London, and getting two scientific verticals online by mid-2027.
- **Scaling the Team**: Aggressively hiring senior scientific and operational talent to build the experimental protocols and finance function.
- **Commercial Model**: Developing and stress-testing a token-based usage pricing model that translates physical lab capacity into customer cost.
- **Grant and Venture Funding**: Managing parallel ARIA and DSIT grants alongside a venture round to fund capital-intensive lab infrastructure.

## Why Work Here
- **High-Impact, Foundational Work**: This is a deeply unusual finance and engineering problem — building the infrastructure layer for AI biology from scratch. The work directly addresses a critical bottleneck in the field.
- **Founding Team & Culture**: The company is led by four co-founders with deep expertise in lab automation (Automata), AI, and biology. The culture is described as hybrid with a strong in-person presence (at least three days a week in King’s Cross).
- **Unique Finance Role**: The Financial Controller role, for example, is described as "the single highest-impact piece of finance work in the company," blending finance, product, and pricing work.
- **Growth Trajectory**: The company is scaling from 4 co-founders to ~32 people by Q1 2027, offering early employees significant ownership and influence.
- **Location**: Based in King’s Cross, London, a major tech and life sciences hub.

## Sources
1. [substratebio.ai](https://substratebio.ai/)
2. [Companies House - Substrate Bio Ltd](https://find-and-update.company-information.service.gov.uk/company/17191596)
3. [Companies House - Officers](https://find-and-update.company-information.service.gov.uk/company/17191596/officers)
4. [AshbyHQ - Financial Controller Job Posting](https://jobs.ashbyhq.com/substrate-bio/a440fcca-aa12-42e6-9997-611463f8ddf4)
5. [AshbyHQ - Chemistry Principal Scientist Job Posting](https://jobs.ashbyhq.com/substrate-bio/7d15e5f9-3f0b-4ad6-abce-c83bf4ed8eb1)
6. [BeBee - Head of Functional Genomics Job Posting](https://bebee.com/gb/jobs/head-of-functional-genomics-substrate-bio-london--theirstack-688561239)
7. [Startuply.vc - Substrate Bio Profile](https://startuply.vc/startup/substrate-bio-u76ba)
8. [Startuply.vc - Article on Substrate Bio Hiring](https://startuply.vc/article/substrate-bio-is-hiring-for-a-fully-automated-wet-lab-that-doesn-t-yet-exist-ioy8to)

## Other roles at Substrate Bio

- [Member of Scientific Staff, Computational Chemistry](https://feeny.ai/job/member-of-scientific-staff-computational-chemistry-substrate-bio-london-gnvrza03pbc9) — London, United Kingdom
- [Member of Scientific Staff, Cell Line Development](https://feeny.ai/job/member-of-scientific-staff-cell-line-development-substrate-bio-london-dpem152a9trk) — London, United Kingdom
- [Member of Technical Staff, Intelligence](https://feeny.ai/job/member-of-technical-staff-intelligence-substrate-bio-london-x22edfw5dq03) — London, United Kingdom
- [Member of Technical Staff,  Intelligence - Functoional Genomics](https://feeny.ai/job/member-of-technical-staff-intelligence-functoional-genomics-substrate-bio-london-hc5g0evaggx7) — London, United Kingdom
- [Member of Technical Staff, Software](https://feeny.ai/job/member-of-technical-staff-software-substrate-bio-london-1ap71r57hp67) — London, United Kingdom
- [Lab Operations Manager](https://feeny.ai/job/lab-operations-manager-substrate-bio-london-6hqtcygvvv2m) — London, United Kingdom
- [Molecular Characterisation Scientist, Biologics](https://feeny.ai/job/molecular-characterisation-scientist-biologics-substrate-bio-london-mtfkrd1s2mqt) — London, United Kingdom