SEEDBiomed · Research Domain

FAIRDatabase

FAIRDatabase — distributed database engineering, queryable encryption and findability for sensitive biomedical data.

Other Domains

BurnsCancerMicrobiomeEndothelial DynamicsFAIRDatabasePharmacology & ToxicologyMetabolic HealthAI for Discovery
2 open projects

FAIRDatabase Projects

01 / 02 Available FAIRDatabase domain illustration

FAIR DATA · Open position

Making FAIRDatabase Interoperable Using Multigres and Streamlining Findability

Scale FAIRDatabase into a distributed, horizontally sharded platform with modern metadata indexing and search APIs across federated instances.

  • FAIR DATA
  • SOFTWARE
Supervisor
V. S. Muniraj
Host
University of Amsterdam · ACTA
Level
MSc
Contact
[email protected]
Read the full project description

High-throughput biological datasets, such as human microbiome profiles, hold enormous potential for disease discovery and personalized healthcare. However, sensitive biomedical data is often fragmented across isolated silos and remains difficult to search, scale, and federate under privacy regulations like GDPR. FAIRDatabase was created as an open-source platform to make human microbiome datasets Findable, Accessible, Interoperable, and Reusable (FAIR) while enforcing strict privacy controls.

As research cohorts grow, there is an urgent need for modern software architectures that can orchestrate queries across distributed nodes and make complex datasets instantly searchable. This project aims to scale FAIRDatabase into an enterprise-grade distributed platform by integrating Multigres for multi-node database orchestration and engineering modern findability pipelines.

Objectives

  1. Integrate Multigres into the FAIRDatabase architecture to support horizontal sharding, intelligent connection pooling, and distributed query execution across multi-tenant database clusters.
  2. Streamline data findability by developing automated metadata indexing pipelines, schema ontologies, and high-performance search APIs that allow researchers to discover and query microbiome datasets across federated instances.
  3. Build and benchmark robust integration connectors and REST/GraphQL APIs that facilitate seamless interoperability with downstream computational pipelines while preserving granular role-based access control and data privacy.

References

  1. Dorst, M., et al. "FAIR compliant database development for human microbiome data samples." Frontiers in Cellular and Infection Microbiology 14 (2024): 1384809.
  2. Supabase / Multigres Team. https://multigres.com/ (2026).
  3. van Eldijk, R., Kumar, S., and Sheraton, V. M. "Integrating microbiome data visualization into FAIRDatabase using edge functions." International Journal of Data Science and Analytics (2026).

Work environment

The student will join an active team of computer scientists and bioinformaticians from the Informatics Institute (IvI) at the University of Amsterdam and ACTA. You will gain hands-on experience in cloud-native technologies, distributed PostgreSQL architectures, Docker orchestration, and API development, directly contributing to open-source infrastructure used by biomedical researchers worldwide.

These descriptions are condensed summaries of the full project proposals and may contain minor errors or be superseded by later revisions. Please confirm the details with the supervisor before applying.

Contact about this project ↗
02 / 02 Available FAIRDatabase domain illustration

FAIR DATA · Open position

Securing FAIR Biomedical Databases: Queryable Encryption and Zero-Trust Architecture

Search sensitive clinical data without ever decrypting it — field-level searchable encryption, identity-bound keys and zero-trust proxying for FAIRDatabase.

  • FAIR DATA
  • SECURITY
  • SOFTWARE
Supervisor
V. S. Muniraj
Host
University of Amsterdam · ACTA
Level
MSc
Contact
[email protected]
Read the full project description

Human omics research holds massive potential for precision medicine, but it relies on sensitive clinical metadata subject to strict privacy regulations such as the GDPR. Open science initiatives demand that this data be FAIR, creating a fundamental engineering challenge: how can researchers securely search and share biomedical data across networks without exposing raw identifiers or decrypting databases in the cloud?

Our team has built FAIRDatabase, an open-source platform designed to store and query biomedical datasets. This project aims to design and implement an end-to-end security and network architecture for FAIRDatabase by integrating state-of-the-art searchable field-level encryption, identity-bound key management, and zero-trust proxying.

Objectives

  1. Evaluate and integrate queryable encryption frameworks (such as CipherStash ZeroKMS and proxy-based encrypted query engines) into the PostgreSQL and Supabase backend of FAIRDatabase, enabling secure equality and range queries directly over encrypted clinical fields.
  2. Design a zero-trust network model and fine-grained authentication layer combining role-based access control (RBAC), mutual TLS (mTLS), and tamper-evident cryptographic audit logs to monitor and isolate sensitive dataset access.
  3. Benchmark the performance, query latency, and network overhead of the hardened architecture under real-world multi-omics query workloads, quantifying the security–utility trade-offs of searchable encryption.

References

  1. Dorst, M., et al. "FAIR compliant database development for human microbiome data samples." Frontiers in Cellular and Infection Microbiology 14 (2024): 1384809.
  2. Fuller, B., et al. "SoK: Cryptographically protected database search." IEEE Symposium on Security and Privacy (2017): 172–191.
  3. CipherStash: Searchable, application-level encryption for building privacy-first apps. https://github.com/cipherstash

Work environment

The student will join an active team of researchers from the Informatics Institute (IvI) at the University of Amsterdam and ACTA. This multidisciplinary group includes experts in AI development and computational biomedicine. You will make direct contributions to an open-source system protecting real-world medical and microbiological data.

These descriptions are condensed summaries of the full project proposals and may contain minor errors or be superseded by later revisions. Please confirm the details with the supervisor before applying.

Contact about this project ↗

Interested in one of these projects?

Every project above has its own supervisor and contact address. If you are unsure which fits you best, or want to propose your own angle, write to the group directly — include your CV, your programme, and which project caught your eye.

Contact regarding a project ↗

[email protected] · SEEDBiomed, Informatics Institute, University of Amsterdam