Head of Protein Science

The opportunity
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Substrate is building a network of fully autonomous wet labs, cloud\-based data production facilities for AI biology, integrated with foundation models to become the critical infrastructure layer for AI\-driven biological discovery. Our first node opens in King’s Cross, London, with several integrated workcells and two scientific verticals online by mid\-2027\. Our customers range from foundation model labs to global pharma.

We are hiring a Head of Protein Science to build and lead the protein vertical from scratch. The vertical covers the full pipeline: expression and purification, biophysical characterisation, cell\-based functional assays, and developability assays. This is the first scientific vertical we are bringing online: manual development is starting now, and full autonomous execution on workcells is targeted for mid\-2027\. You will own the assay menu, scope it against early customer demand, shape the workcells the assays will eventually run on, and build the team that operates the function at scale. You will be the senior protein scientist in the company at hire.

About Substrate
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Substrate is spinning out of Automata, the UK lab automation company that has built the workcell platform our labs run on. Our four co\-founders are Mostafa ElSayed (CEO and founder of Automata), Oli Hoy (formerly VP Customer Experience at Automata), Alexey Morgunov (AI Scientist co\-founder, leading the intelligence software product), and a Founding Biology Lead joining shortly. We are aiming to have ramped up to 32 people by the end of Q1 2027\.

We are funded in parallel by a combination of venture funding and government grants. We are not a cloud lab and we are not a CRO. We are an autonomous lab platform with closed\-loop integration available as one operating mode for foundation model partners.

The role
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You will own protein science end\-to\-end. Day one priorities are the scientific pieces of standing up a vertical from scratch: scoping the priority assay menu against early customer demand, developing and validating those assays manually, setting quality thresholds, and hiring the Principal Scientists, Scientists, and Lab Technicians who will operate the function at scale. The vertical will eventually span expression and purification across multiple host systems, biophysical characterisation, cell\-based functional assays, and developability assays for customers taking constructs toward the clinic; the day\-1 wedge is a focused subset of that menu, and you decide where to start.

Two parts of the role are not standard, and they are why this role is so crucial to Substrate’s success. The first is that the protein vertical is being built AI\-first from day one. Every assay is designed from scratch for full AI\-in\-the\-loop automation, not retrofitted onto a manual workflow. You do the assay by hand first, exactly as you would in a high\-end pharma research lab, and then work with Automata’s automation scientists to shape the workcells the assays will eventually run on. You will define the quality thresholds for each transition stage, decide which manual judgement calls have to be re\-engineered out, and own the validation that proves equivalence at each step.

The second is closed\-loop work with foundation model partners. Substrate’s distinctive operating mode is producing structured, machine\-readable experimental data fast enough to feed directly into foundation model training. That changes how protein assays get designed: output structure, metadata, provenance, and consistency across runs become first\-class scientific constraints. You will work directly with model partners on protocol co\-design, and with our software and intelligence teams on how the resulting data flows back into customer pipelines and into Substrate’s own data factory.

You will also be the executive partner to the co\-founders on anything protein\-science related: the assay roadmap, the proprietary protein dataset programme on the reserved fraction of lab capacity, and the customer conversations where protein science depth is decisive.

What you will do in your first twelve months
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PHASE 0: NOW TO AUG 2026
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• Land in the lab. Set up workspace at our King’s Cross site and start manual assay development.


• Lock the day\-1 assay menu against early customer demand. Decide the order in which expression, purification, biophysical characterisation, and the first cell\-based functional readouts come online.


• Hire the first Principal Scientist and Lab Technician alongside you. Define the roles, run the processes, close the offers.

• Develop and validate the first protein assays manually. Set the reproducibility and quality thresholds that will serve as acceptance criteria for the moves to instrumented and to fully autonomous execution.


• Co\-design protocols with the software and automation engineering teams so that the manual versions you validate are automation\-ready by design. Decide which manual judgement calls have to be engineered out before they hit a workcell.


• Begin co\-design conversations with the first commercial customers, including the foundation model partners coming online from mid\-2027\.

• Workcells arrive in the lab. Move the validated assays onto them, running with instrumentation and human intervention in the loop ahead of full autonomous operation. Validate equivalence against the manual baselines.


• Grow the team. Bring on the second Principal Scientist and the first scientists at the bench to support throughput as the assay menu opens to customers.


• Ship the first revenue on the protein vertical from manual and semi\-automated services.

You are an experienced protein scientist who has built or led an assay function in a pharma R\&D, biotech, or CRO setting. You are comfortable in the detail at the bench and you are comfortable setting direction for a team. The shape of the problem is what attracts you: an assay portfolio that has to be designed for autonomous execution from day one, in a business where the data the lab produces is itself part of the product.

You have hired and managed scientists, principal scientists, and technicians. You have set quality thresholds and held people to them. You have run assay portfolios that supported real customers, internal teams in pharma or external customers in a CRO setting, and you understand what enterprise\-grade scientific operations look like.

You are pragmatic about being hands\-on at the bench in the first six to nine months, and excited about the team you will build behind you. You enjoy interviewing, hiring, mentoring, and setting standards. You will be in the lab at our King’s Cross site at the cadence the science demands. That cadence will be heavy in the manual development phase and ease as the function grows and protocols move onto instrumentation. You are comfortable with that.

MUST HAVE
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• Seven or more years of experience in protein science, with at least three in a senior or team\-leading role at a pharma R\&D, biotech, or CRO organisation.


• End\-to\-end hands\-on experience in at least one modality (antibodies or analogous), covering expression, purification, and biophysical characterisation, with working familiarity across cell\-based functional assays and developability assays.


• Track record of leading a small scientific team end to end: hiring, setting quality standards, and managing performance against scientific outputs.


• Customer\-facing experience, either as a CRO scientific lead working with external customers, or as a pharma scientist embedded with internal customer teams.

• Direct experience moving protein assays from manual workflows onto lab automation platforms.


• Familiarity with structured experimental data capture, LIMS, ELN, or analogous data infrastructure.


• Experience working with computational or AI/ML colleagues on closed\-loop assay programmes.


• Background at an AI\-native biotech or foundation model company.

Most senior protein science roles in industry sit either inside a pharma R\&D group (slow iteration, internal customers only) or inside a CRO (external customers, faster iteration, but optimised for service throughput rather than scientific decisions about assay design). This is neither. You will be designing an assay menu that has to be automation\-ready from the first manual experiment, working with foundation model labs on closed\-loop programmes that do not have a precedent in either pharma or CRO settings, and owning the proprietary dataset programme that turns the lab itself into a commercial asset.

It is also a protein science role with significant software and AI surface area. Your assay decisions affect what the orchestrator has to do, what data flows back to model partners, and which manual judgements get re\-engineered out of the workflow. Some scientists find that energising; some find it outside their lane. Worth knowing in advance which one you are.

Compensation and equity
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We pay competitively against the London market for senior protein scientists at venture\-backed companies, calibrated to seniority and to the specific scope of this role. We will discuss numbers with serious candidates after first conversations.

Equity is meaningful, with vesting on the standard four\-year schedule and a one\-year cliff. We can talk through the philosophy and the maths in detail when we meet.

How we work
===============

Working pattern is hybrid with a strong in\-person bias dictated by the lab. In the manual development phase you will be at our King’s Cr

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