Software Engineer - Data Discovery

EMBL-EBI - European Bioinformatics Institute

Hinxton, United Kingdom

We are looking for a Software Engineer to join our Pathogen Data Network project. Our group provides worldwide reference data resources in interactomics (IntAct), pathways (Reactome), and systems biology models (BioModels), as well as infrastructure for biomedical knowledge management in the EBI Search and identifiers.org projects.

Your role

In an international context, you will implement advanced indexing strategies and support the integration of multi-modality data across molecular biology and related disciplines into complex web portals. You will contribute to resources which support international biomedical research.

In this exciting new role you will have the chance to:

Contribute to the development of lightweight, efficient structures for the integration of data from multiple different domains;
Communicate with internal, as well as external data providers across and beyond Europe to support them in developing optimal data discovery strategies;
Contribute to the integration and indexing of the data, as well as providing it through user-friendly web interfaces and web services to the international research community;
Collaborate with colleagues, using industry-standard best practices to create and maintain efficient, reusable and well-documented software.

On the conceptual level, you might have the opportunity to contribute to strategies using Machine Learning to optimise data discovery and user experience

You have

Degree in computer science or a related field;
minimum two years experience in software development;
good knowledge of Java;
experience with JavaScript/TypeScript;
good communication skills;
Familiarity with current coding practices and development tools, including version control, CI/CD, etc.

You might also have

Experience in biomolecular or biomedical data and metadata integration;
Working knowledge of Lucene or Lucene-based search engines;
Knowledge of other data storage technologies (RDBMS, graph databases, NoSQL);
Some DevOps knowledge;
Familiarity with Linux/Unix-based systems;
Experience in collaborative development tools like Jira and Confluence to track your work;
Use of Machine Learning, ideally in a data discovery context.

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