Postdoc in Data Harmonization: KTH Royal Institute of Technology in Stockholm invites applications for a post-doctoral position in Multimodal Clinical Data Harmonization and Knowledge Graphs. The role focuses on developing a platform for integrating and analyzing medical data across various modalities using advanced knowledge graph approaches, graph neural networks (GNNs), and uncertainty-bounded prediction techniques.
This is a highly interdisciplinary research position that provides the opportunity to collaborate with leading researchers in clinical data and innovative technologies in an international and creative work environment.
Postdoc in Multimodal Clinical Data Harmonization and Knowledge Graphs
Designation
Post-Doctoral Research Fellow
Research Area
- Multimodal clinical data harmonization.
- Knowledge graphs and graph neural networks.
- Machine learning for medical or clinical data integration and analysis.
- Uncertainty-bounded predictions in graph representation and learning tasks.
Location
Stockholm, Sweden
Eligibility/Qualifications
| Category | Requirement |
|---|---|
| Minimum Education | Doctoral degree (or equivalent foreign degree) in a relevant field. |
| Experience | Research expertise in data management, machine learning, knowledge graphs, and graph neural networks. |
| Technical Skills | Strong programming skills and familiarity with production environments and open-source tools for ML & GNN. |
| Academic Skills | Track record of leading academic writing tasks, such as conference papers and journal articles. |
| Preferred Qualification | Doctoral degree obtained in the last 3 years and a strong publication record. |
| Other Requirements | Good communication and collaboration skills, command of English, and awareness of diversity and equal opportunities. |
Job Description
The appointed post-doctoral researcher will lead the development of a unified hierarchical knowledge graph platform for harmonizing, integrating, and analyzing medical data. Key responsibilities include:
- Utilizing medical ontologies to integrate data across diverse clinical domains such as genomics, imaging, and clinical records.
- Employing graph neural networks to reveal hidden insights and predictive explorations in healthcare.
- Developing data models with reduced data requirements through enhanced graph representation learning.
- Incorporating uncertainty estimation methods to improve trust and accountability in predictive systems.
- Collaborating within an interdisciplinary research environment to achieve project goals.
This position is temporary and intended as a stepping stone for an early-career researcher after completing their doctoral studies.
What KTH Offers
- A position at one of Europe’s leading technical universities.
- Opportunities for dynamic, interdisciplinary research involving leading-edge technologies.
- A creative, international work environment in a vibrant city close to nature.
- Support for relocation and settling in Sweden.
- A workplace that values diversity, gender equality, and a bias-free approach.
How to Apply
To apply for this position, log into the KTH recruitment system and submit a complete application with the following documents:
- CV containing details about professional experience and knowledge.
- Copy of diplomas and grade transcripts (translated to English/Swedish if necessary).
- A brief account (maximum 2 pages) outlining:
- Why you wish to conduct research in this area.
- Your academic interests and their relation to your previous studies and long-term goals.
Last Date for Application
28th February 2025 (midnight CET/CEST).
About KTH
KTH Royal Institute of Technology is one of Europe’s top engineering and technology universities and the largest technical education and research institution in Sweden. Renowned for sustainability-driven innovation, KTH offers a diverse, interdisciplinary environment for researchers from across the globe.
For further inquiries, contact:
- Sebastiaan Meijer: +46 879 08071, smeijer@kth.se
- Paris Carbone: parisc@kth.se
For more details and to apply, visit the official KTH job application page.
Note: KTH is committed to equal opportunities and strives towards gender equality and inclusivity in all its activities.
