Functional Genomics Scientist

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.

Functional genomics is the second scientific vertical we are bringing online, alongside protein science. The vertical covers cell line engineering, perturbation library design, screen execution, and bulk and single\-cell sequencing readouts, with the resulting data feeding customer pipelines that include foundation model training for virtual cell models. Manual development of the day\-1 screening workflowSubstrate 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\. is starting now, and full autonomous execution on workcells is targeted for mid\-to\-late 2027\. You will be the bench scientists who develop, validate, and operate the screens through that transition: running them by hand, setting reproducibility and quality thresholds, working alongside automation engineers as the screens move onto instrumentation, and validating equivalence at every step. The Head of Functional Genomics you will work under is being hired alongside you.

About Substrate
===================

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 be at the bench. The work is to develop, validate, and operate the screens that will eventually run autonomously on Substrate’s workcells. In the first phase, that means manual screen development: cell line preparation, library cloning and QC, lentivirus production, screen execution, sequencing sample prep, and the readout pipeline — all by hand, setting reproducibility and quality thresholds, and proving each step out before it moves onto instrumentation. As the workcells arrive, 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 alongside Principal Scientists at the bench, executing the experiments, contributing to validation work, and growing into protocol authorship over the first year. You will work directly with our automation engineering and software teams on the boundary between scientific protocols and autonomous execution.

What is unusual about the work is that no screen 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 screen produces — cell line provenance, library composition, perturbation metadata, sequencing QC, consistency across runs — is treated as a first\-class scientific constraint, because that data feeds directly into foundation model training pipelines for our customers. Your decisions at the bench affect what the orchestrator has to do and what data flows back to model partners.

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 your bench at our King’s Cross site and start manual screen development alongside the Head of Functional Genomics.


• Get hands on the day\-1 wedge as the Head scopes it: which cell line, which library, which sequencing readout. Run the early steps by hand and capture the data structure and metadata decisions that will translate to workcell design.

• Develop and validate the first screens 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.


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

• Workcells arrive in the lab. Move the validated screens onto them, running with instrumentation and human intervention in the loop. Validate equivalence against your manual baselines and triage failures.


• Open the screening menu to customers via manual and semi\-automated services. Run real experiments for real customers.


• Help bring on the next Scientists and Lab Technicians as the vertical grows.

You are a functional genomics scientist who is excited about doing the actual work — designing, running, validating, and iterating on screens at the bench. You are comfortable in the detail. You have done at least one screening modality end to end. The shape of the problem is what attracts you: screens that have 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 write good SOPs. You hold yourself and your colleagues to clear reproducibility thresholds. You are pragmatic about being hands\-on in the early phase, with cadence that will be heavy in the manual development phase and ease 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 with them.

We are hiring across both Scientist and Principal Scientist levels. The shape of the work is similar at both tiers: hands\-on bench science, with collaboration into automation and software. The difference is depth of ownership and team responsibility.

MUST HAVE
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• Hands\-on cell culture experience, including CL2 wet\-lab work with mammalian cell lines.


• Hands\-on experience in at least one component of pooled screening: cell line preparation, library cloning and QC, lentivirus production, screen execution, or sequencing sample prep.


• Comfortable executing protocols at the bench through manual, semi\-automated, and instrumented phases.


• Track record of working alongside non\-scientist colleagues (automation, software, computational) on a shared workflow.


• Three or more years of post\-PhD or equivalent industry experience in functional genomics, cell biology, or molecular biology with a screening\-adjacent focus.


• Strong hands\-on competence in cell culture and in at least one of: library cloning, lentivirus production, single\-cell capture, or NGS sample prep.


• Ready to grow into protocol authorship and SOP ownership over the first 12 months.

• Hands\-on experience in cell line engineering, particularly iPSC differentiation or CRISPR\-edited stable cell line generation.


• Direct experience moving screens 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 perturbation programmes.


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

Most functional genomics bench roles in industry sit either inside a pharma R\&D group (slow iteration, internal customers only), inside a CRO (external customers, faster iteration, but optimised for service throughput rather than scientific decisions about screen design), or inside an AI\-native biotech (fast iteration, but a single internal customer in the company’s own pipeline). This is none of the three. You will be developing screens that have to be automation\-ready from the first manual experiment, working alongside foundation model labs on closed\-loop programmes that do not have a precedent in any of those settings, and contributing to the proprietary dataset programme that turns the lab itself into a commercial asset.

It is also a functional genomics role with significant software and AI surface area. The way you design and run screens affects 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 functional genomics scientists at venture\-backed companies, with bands calibrated to seniority and to the specific scope of the role. We will discuss numbers with serious candidates after first conversat

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