Member of Scientific Staff, Computational Chemistry

LOCATION: King’s Cross, London · PATTERN: Hybrid, flexible for the right candidate The opportunity We’re a stealth startup in AI and bio, building infrastructure for data generation. The team is small and elite, the problems are hard, and the foundations are being laid right now. You’d help write them from the first line, with real ownership and a direct line to the founders. This role builds our computational chemistry from the start. You would own how a set of target molecules becomes a synthesis plan that automated equipment can run, and how every compound we work with is represented and registered.

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 own computational chemistry end to end, from the molecules someone wants made to the plan the lab executes.

The role

sits at the interface between synthetic chemistry, cheminformatics and software, and lab automation, and you will build the computational capability alongside the physical synthesis and automation capability from an early stage.

The role

is embedded with the synthetic chemists and the automation scientists and engineers, and you will work with them every day. Much of the value comes from drawing out what experienced chemists know and turning their judgement into rules, models and workflows that apply the same way every time. Two parts of the role go beyond standard computational chemistry, and they are why it matters so much. Routes that automation can execute. A chemically plausible route is only the starting point. Planning has to account for what the platform can do, including the building blocks and reagents available, the reaction classes and conditions it supports, handling constraints, work-up and purification, and throughput. It also has to work across a whole target set. Given hundreds or thousands of targets, you will find the shared chemistry, common intermediates and building blocks, and reduce them to a manageable set of synthetic strategies, balancing diversity and compound value against synthetic cost. You will work with the automation team to define what planning hands to the systems downstream, and over time connect planning, synthesis and experimental results so that each round of results improves the next plan. Chemical identity from the outset. The digital representation and identity of compounds has to be right from the start, because other scientific teams will rely on compound registration for chemical identity, as well as synthesis planning. You will establish when two structures represent the same chemical entity and when they do not, and handle stereoisomers, salts, tautomers, protonation and charge states and other representation and normalisation questions consistently. You will be the first person in this seat. You will choose the methods, set the standards, write the first production code and shape how the capability grows, including who joins it. Your first 90 days FIRST 30 DAYS ◆ Learn how the synthetic chemists and the automation team work, and what the synthesis platform will and will not support. ◆ Agree the rules for chemical identity with the chemists, covering structure normalisation, validation and deduplication, and how stereochemistry, isomers, salts, tautomers and charge states are handled. ◆ Start ingesting vendor catalogues and building-block inventories through supplier APIs and external chemical data sources, capturing availability, cost and metadata so they can act as planning constraints. ◆ Agree with the automation team what a synthesis plan has to specify for the platform to execute it. DAYS 30 TO 60 ◆ Set up compound-registration workflows and identifiers that downstream systems can rely on. ◆ Run a first planning pass on a real target set, generating, evaluating and ranking routes and grouping targets by shared chemistry, intermediates and building blocks. DAYS 60 TO 90 ◆ Build the platform’s capabilities and constraints into planning, so routes are scored on whether they can be executed as well as whether they are plausible. ◆ Add selection across the target set that weighs diversity and compound value against synthetic cost, step count and throughput. ◆ Connect compounds, reactions and experimental results to the wider digital chemistry stack (ELN, LIMS and compound registration), and set out how results will feed back into the route and reaction models.

Who you are

You work across disciplines. You might be a computational chemist or cheminformatician who has spent real time with synthetic chemists, or a synthetic chemist who moved into modelling and software and still cares whether a route works at the bench. You have built synthesis-planning or chemical-data tools that other people relied on, and you know where they break. You think in sets of molecules as well as single ones. You are comfortable making decisions on incomplete information, writing them down, and changing them when the data says so. You listen carefully to chemists, because much of what this role needs is in their judgement and has never been written down. This is a founding seat. You will lead the computational side of our chemistry, and we expect you to shape it from your first week. Nobody arrives with every part of this role. If you are strong in most of it and quick to learn the rest, we want to hear from you. We do not hire people into boxes. This role will stretch past its description, into the lab and into how other teams use chemical data, and early hires here pick up what is in front of them. MUST HAVE ◆ Enough grounding in synthetic organic chemistry to speak the language of synthetic chemists, draw out and distill their expertise, and translate practical chemical judgement into computational rules, models and wor