Bioinformatician – Structural Proteomics & Integrative Modelling

We are seeking a Bioinformatician with expertise in structural biology, proteomics and integrative/hybrid structure modelling 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 maintain the global archive of experimentally determined macromolecular structures, the Protein Data Bank (PDB).

We also manage the community-led PDBe Knowledge Base (PDBe-KB) and the Alpha Fold Protein Structure Database (AFDB), a collaboration with Google Deep Mind. The team brings together scientists, software engineers and data engineers to develop tools and services for structure deposition, data integration, advanced search and biological interpretation.

This is an exciting opportunity to develop FAIR infrastructure for structural interactomics and integrative/hybrid modelling. The project will connect experimental proteomics evidence, including crosslinking mass spectrometry (XL-MS), co-fractionation mass spectrometry (CF-MS) and affinity-purification mass spectrometry (AP-MS), with structural restraints, predicted structures, integrative models and molecular interaction data.

Working in close partnership with colleagues in PRIDE and wwPDB, you will help establish the data standards, deposition workflows, validation approaches and access services needed to make these interconnected datasets discoverable, interpretable and reusable. The role is ideal for a scientist who enjoys working across disciplines and wants to make a lasting contribution to open scientific infrastructure.

You will contribute to the development of standards and infrastructure that connect structural interactomics experiments, proteomics evidence and integrative structure models. You will work at the interface of structural biology, proteomics and scientific software development, applying both biological understanding and technical expertise to improve the interoperability, provenance and reuse of these data.

• Analyse current XL-MS, CF-MS, AP-MS and integrative modelling workflows to define data and metadata requirements.
• Contribute to the extension and adoption of community standards for structural interactomics and integrative modelling data.
• Develop data models and interoperable software tools that connect proteomics and structural biology formats, including suitable conversion of proteomics outputs into integrative modelling representations.
• Develop and maintain tools, APIs, workflows and documentation that support standard-compliant data deposition and local validation.
• Implement approaches for cross-modality validation, identifier mapping and provenance tracking between experimental evidence, structural restraints and integrative models.
• Work with PRIDE and PDB-IHM colleagues to establish linked deposition, release and access workflows across relevant resources.
• Contribute to integrated search, visualisation and programmatic access services for structural interactomics data.
• Engage with researchers, analysis-tool developers and standards communities to support testing, adoption and further development of the infrastructure.
• Contribute to scientific publications, technical documentation, training and dissemination activities.

• PhD in Bioinformatics, Computational Biology, Structural Biology, Proteomics, Computer Science or a related field.
• Familiarity with structural biology, protein structure or molecular interaction data.
• Experience working with biological data, metadata, identifiers and scientific repositories.
• Understanding of sequence, structure and functional annotations of proteins.
• Experience in scientific software development, preferably using Python.
• Experience designing or implementing data-integration workflows, APIs or data-processing pipelines.
• Familiarity with FAIR data principles, metadata standards and reproducible research practices.
• Experience with Linux environments, Git, testing and documentation practices.
• Scientific publications relevant to structural biology, bioinformatics, proteomics or biological data resources.
• Strong communication, collaboration and problem-solving skills.

• Familiarity with integrative/hybrid modelling, structure prediction or macromolecular modelling.
• Experience with mass-spectrometry-based proteomics,…