PhD FAIR rare disease data to accelerate diagnosis and treatment

Rare diseases present unique challenges in both clinical and research settings due to the limited number of patients affected by each condition. Despite this, the sheer number of rare diseases collectively affects a significant portion of the population, with an estimated 30 million patients in Europe. The goal of this PhD project is to explore how FAIR (Findable, Accessible, Interoperable, Reusable) principles can be applied to make data from rare disease patients more useful for clinical research methodologies, which typically require larger patient populations. 

The research will delve into how community standards (such as SNOMED CT, OBO, ICD) can be harmonized to ensure the reuse of biomedical data beyond individual use cases. A critical part of the project will focus on understanding the nuances in terminology across different standards and developing methods to map and reuse identifiers, taking into account the varying contexts of these terms. You will work on applying traditional and novel techniques, including from the field of artificial intelligence, to expedite and improve the “FAIRification” of rare disease data, ensuring it can be more widely accessed by the scientific community while respecting privacy, legal, and ethical considerations.  

Want to read more about a PhD in Amsterdam UMC? See this page for more information. 

You will conduct research on the following key areas:

• Identifier Mapping: Investigating the challenges of mapping biomedical identifiers across different data sets and standards, ensuring accurate representation of data in diverse research contexts;
• Ontology Design and Ontology Mapping: Developing and reusing ontologies that facilitate the integration and interpretation of biomedical data primarily by improving interoperability;
• Digital Preservation of Biomedical Data within Legal and Privacy Frameworks: Ensuring that biomedical data, particularly from rare disease populations, is preserved and accessible in accordance with legal, ethical, and privacy guidelines;
• Persistence Management of Machine-Readable Knowledge Repositories: Designing strategies to maintain the long-term accessibility and usability of machine-readable biomedical data repositories, supporting the ongoing FAIRification process.

As a PhD student on this project, you will:

• Investigate how data on rare diseases can be made more FAIR;
• Develop and apply efficient methods to implement FAIR principles for small patient populations to support clinical research;
• Work on mapping and reusing biomedical terminologies, with a focus on context-sensitive harmonization between standards;
• Explore how to increase the exposure of rare disease data to a broader audience of scientists while adhering to privacy and legal regulations;
• Develop semantically rich schemas and ontological models to enhance the FAIRness of collected project data.

Furthermore, you will: 

• Conduct your research within an active group at the department of Medical Informatics;
• Work within a collaborating European network of scientists working on Rare Disease research, including in the ERDERA project;
• Disseminate your results at (inter)national conferences and publish your work in peer-reviewed journals.

You are motivated and enthusiastic to perform PhD research and passionate about improving care for patients with rare diseases. You aspire to make a meaningful contribution to the fields of medical informatics and rare diseases by combining theory, practice, and technology. 

Prerequisites: 

• Master's degree in (bio)medical informatics, cheminformatics, data science or related fields;
• Strong interest in rare diseases and biomedical data;
• Strong analytical and programming skills and the ability to work independently as well as in a collaborative environment;
• Excellent English communication skills, both written and verbal.

Not required, but helpful:

• Familiarity with data governance principles, GDPR, GCP, and/or FAIR data principles;
• Knowledge on community standards such as SNOMED CT, ORDO, OBO and ICD is a plus;
• Affinity and preferably experience with writing research papers;
• Proficiency in Dutch.

Please upload CV and cover letter in English due to English speaking selection committee member.