Bindbridge
Computational Structural Biologist
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Computational Structural Biologist
# Computational Structural Biologist
Type: Full-time Location: Remote (UK/EU-based) Compensation: Competitive (plus equity commensurate with experience)
About Bindbridge
Bindbridge is advancing sustainable agriculture through AI-powered molecular glue discovery. Backed by Speedinvest and Nucleus Capital, we are building a computational platform to bring targeted protein degradation to agriculture.
The Role
We are seeking an experienced Computational Structural Biologist with a strong background in protein–protein interaction modelling and a deep understanding of protein structure. This is a unique chance to directly shape our induced proximity computational platform, from defining structural and biophysical data needs to interpreting results and translating insights into improved machine learning (ML) models.
Molecular glues work by stabilising protein-protein interactions that are often weak, transient, or difficult to observe. Predicting when these interactions form productive complexes—and how they affect cooperativity, affinity, and biological outcomes—remains unresolved. In this role, you will:
- Build computational and data foundations to make these interactions more predictable.
- Work across data generation strategy, structural interpretation, model validation, and ML model refinement.
Key Responsibilities
- Own computational structural biology projects end-to-end, translating requirements into validated, production-grade workflows with full autonomy.
- Develop computational approaches for induced proximity, focusing on modelling weak/transient protein-protein interactions, and convert prototypes into robust, reusable code.
- Apply machine learning, co-folding, protein docking, and molecular dynamics to integrate experimental data into predictions of structure, cooperativity, and binding affinity.
- Query structural/sequence databases and build large-scale data pipelines for model training, benchmarking, and evaluation.
- Interpret structural/biophysical data and translate biological insights into next-gen ML models for induced proximity.
- Collaborate with experimental scientists to design data collection and validation strategies.
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Requirements
Essential
- PhD or MSc in Structural Biology, Biochemistry, Biophysics, Chemistry, Bioinformatics, or a related field.
- Experience in both academia and industry (preferably biotech), with at least 2 years of postgraduate industrial work.
- Strong working knowledge of structural/biophysical datasets, including cryo-EM, XL-MS, and SAXS, with hands-on experience in data collection/analysis and structure determination.
- Exceptional Python programming skills, including CI/CD and cloud infrastructure (e.g., GCP, AWS).
- Expertise in building reproducible, scalable computational/structural biology workflows.
- Proficiency in modern protein structure prediction/co-folding (e.g., AlphaFold, Boltz, Chai-1) and downstream methods (e.g., docking, molecular dynamics).
- Strong communication, documentation skills, and a bias for reproducibility/collaboration.
- Proactive, delivery-driven mindset and passion for enabling scalable, cutting-edge research.
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Nice to Have
- Experience with induced proximity modalities, such as PROTACs, molecular glues, and bifunctional molecules.
- Background in industry drug discovery (structure-based design, PPI modulation, targeted protein degradation, or related fields).
- Experience with cloud-based infrastructure.
- Familiarity with agile project management.
Why Join Us?
- Competitive salary (plus equity) aligned with experience.
- Fully remote work, with quarterly on-site meetups.
- Support for conference attendance, publications, and patents.
- Help shape AI-driven molecular discovery in agriculture, addressing global food security challenges.
Application Process
- CV review: Look for relevant expertise, motivation, and mission alignment.
- First interview: Informal chat with a team member to discuss background and interests.
- Technical interviews:
- Two interviews covering algorithm design and experimental validation with engineering/research teams.
- Final interview: Discussion with a founding team member.
- References & offer: References checked; offer extended if aligned.
Bindbridge is an equal-opportunity employer. We welcome candidates from all backgrounds and are committed to an inclusive, respectful, and high-performing team.
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