Bioinformatician in Saffron Walden

We are seeking a Bioinformatician with expertise in data integration and experience in structural biology and molecular dynamics (MD) data to join the Velankar team at the European Bioinformatics Institute (EMBL-EBI). The Protein Data Bank in Europe (PDBe) team develops essential macromolecular structure resources and tools for biologists and other life scientists. As a founding partner of the Worldwide Protein Data Bank, we are responsible for maintaining the global archive of experimentally determined macromolecular structures, the Protein Data Bank (PDB). We also manage the community-led PDBe Knowledge Base (PDBe-KB) resource and the AlphaFold Protein Structure Database (AFDB), a collaboration with Google DeepMind.

The PDBe team consists of an international and interdisciplinary group of scientists, software engineers, and data engineers who develop a range of tools and services that support structure deposition, data integration, and advanced search capabilities for structural biologists and the wider life sciences community.

This position offers an exciting opportunity to contribute to the Horizon Europe-funded MD4SB (Molecular Dynamics for Structure-Based Biology) project. MD4SB is a major European research infrastructure initiative aiming to transform structural biology by integrating molecular dynamics simulation data into the wider life sciences ecosystem.

Your role will involve:

• Contributing to the development of infrastructure connecting molecular dynamics simulations with structural biology resources and biological knowledge bases.
• Developing AI-driven approaches to mine scientific literature and automatically extract experimental and biological metadata to enrich MD datasets.
• Developing and extending SIFTS (Structure Integration with Function, Taxonomy and Sequence), a core PDBe resource that provides residue-level mappings between PDB structures, UniProtKB sequences, and other biological resources.
• Applying both scientific understanding and technical expertise to develop data integration workflows, APIs, and biological annotations that improve interoperability and reuse of structural and molecular simulation data across various resources.

Primary responsibilities include:

• Designing and implementing data integration pipelines that connect MDDB with major life science resources, including PDBe, UniProt, PDBe-KB, and other relevant knowledge bases and databases.
• Developing and deploying AI- and machine learning-based approaches for extracting experimental and biological metadata from scientific literature to enrich MDDB datasets.
• Extending and maintaining the SIFTS infrastructure and codebase to support integration of molecular dynamics and other data resources.
• Developing and maintaining software tools, APIs, workflows, and documentation that facilitate FAIR data integration, metadata enrichment, and integrated data access.
• Collaborating with domain experts, software engineers, and data resource providers to enable the integration of MD-derived biological insights into the wider life sciences data ecosystem.
• Supporting FAIRification, standardisation, and interoperability of MD datasets and associated annotations.
• Collaborating with international partners across ELIXIR, Instruct-ERIC, EU-OPENSCREEN, HPC centres, and industry.
• Participating in community standards development, technical documentation, training, outreach, and dissemination activities.

You have:

• PhD in Bioinformatics, Computational Biology, Structural Biology, Computer Science, Data Science, or a related field.
• Familiarity with structural biology and molecular simulation data.
• Experience with NLP/LLM-based scientific literature mining.
• Demonstrated experience with FAIR data principles, metadata standards, and scientific repositories.
• Understanding of sequence, structure, and functional annotations of proteins.
• Experience in scientific software development, preferably in Python.
• Experience with Linux environments, Git, and CI/CD practices.
• Strong communication, collaboration, and problem-solving skills.

You may also have:

• Postdoctoral research experience in a relevant field.
• Experience with graph databases (e.g. Neo4J), REST APIs, containerisation technologies, and workflow management systems such as Nextflow.
• Experience in data visualisation and analysis.
• Understanding of FAIR data principles and the biological data lifecycle.
• Experience in reporting and presenting scientific topics.
• Experience working in international and interdisciplinary teams.

Benefits and Contract Information:

• Financial incentives: depending on circumstances, monthly family/marriage allowance of £291, monthly child allowance of £351 per child, non-resident allowance up to £595 per month.
• Annual salary review, pension scheme, death benefit, long-term care, accident-at-work and unemployment insurances.
• Hybrid working arrangements.
• Private medical insurance for you and your immediate family (including all prescriptions and generous dental & optical cover).
• Generous time off: 30 days annual leave per year, in addition to eight bank holidays.
• Relocation package including installation grant (as applicable).
• Campus life: Free shuttle bus to and from work, on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely).
• Family benefits: On-site nursery, child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances.
• Contract duration: This position is a 3-year contract.
• Salary: Monthly salary starting at £3,303 - £3,695 after tax (but excluding pension & insurances) + benefits.
• International applicants: We recruit internationally and successful candidates are offered visa exemptions.
• Diversity and inclusion: At EMBL-EBI, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought.
• Job location: This role is based in Hinxton, near Cambridge, UK.

To apply, please submit a covering letter and CV via our online system. Applications will close on 04/09/2026. We will review applications on a rolling basis and reserve the right to close the vacancy earlier than the published closing date.