Senior Computational Biologist
Type: Full-time
Location: Remote (UK/EU based)
Compensation: Competitive (plus equity)
About us
I’m working with an ag-biotech at the forefront of sustainable agriculture, using AI-driven molecular glue discovery to bring targeted protein degradation to crops, pests, and pathogens.
Backed by leading VC’s and currently at seed stage, they’re building a computational platform with the potential to fundamentally change how crop protection works – starting with a new class of herbicides designed to be both highly effective and environmentally responsible.
The Problem You’ll Be Solving
The central challenge involves predicting and modelling weak, transient protein-protein interactions – a fundamentally harder problem than standard PPI docking, which assumes stable complexes.
The interactions this role focuses on are only reinforced once the molecular glue is introduced, which makes computational prediction significantly more difficult.
This is not a role for someone looking to apply established methods to well-defined problems.
What You’ll Be Doing
You’ll own a major initiative end-to-end – from understanding a loosely defined scientific problem through to delivering working solutions. There are no direct reports and no handholding. The expectation is clear: you take the problem, you figure out the approach, and you deliver.
This workstream is tightly linked to customer deliverables, so the impact is immediate and visible.
What We’re Looking For
- Deep experience in protein-protein docking, specifically with weak and transient interactions – this is essential and the central technical requirement of the role
- Solid grounding in targeted protein degradation – molecular glues, PROTACs, E3 ligases, and degron biology
- Confident working with structural biology databases independently – PDB, Pinder, Plinder, degron databases
- Strong Python across two areas: building large-scale protein data pipelines from scratch, and writing well-structured prototype code that a software engineer can take and scale
- The ability to read the literature, identify what’s relevant, evaluate trade-offs, and turn that into immediate deliverables
Bonus points for direct experience with molecular glues or PROTAC-based degradation, familiarity with tools like AdaptivePELE, or exposure to protein structure prediction.
What We’re Not Looking For
This is not an ML-first or pure software engineering role. The biology has to come first. If you need a well-scoped problem and close technical oversight to do your best work, this probably isn’t the right fit.
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