Publisher
source

University of Luxembourg

Postdoc in Health-Data Harmonization and Analysis University of Luxembourg in Luxembourg

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

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Country

Luxembourg

University

University of Luxembourg

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Keywords

Computer Science
Biomedical Engineering
Information Technology
Biology
Translational Medicine
Digital Health
Medical Science
Clinical Informatics
Data Quality
Data Standards
Data Harmonization
Statistics
Bioinformatic
ML

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About this position

Postdoctoral Researcher in Health-Data Harmonization and Analysis at the University of Luxembourg, Luxembourg Centre for Systems Biomedicine (LCSB).

This postdoc sits within the Clinical and Translational Informatics group led by Dr. Venkata Satagopam and focuses on building secure, interoperable, and scalable infrastructures for clinical and biomedical data. The project is highly interdisciplinary and combines bioinformatics, data science, health data interoperability, and AI/ML-enabled analysis to support translational medicine and digital health.

The successful candidate will work on federated data analysis and harmonisation of diverse biomedical datasets, with an emphasis on privacy-preserving and FAIR data use. Key technical areas include OMOP CDM, HL7 FHIR, DICOM, GA4GH standards, HealthDCAT-AP, DPV, ORDL, and data catalogue development aligned with TEHDAS 2 and EHDS requirements. The role involves collaboration with clinicians, data providers, software engineers, and biomedical researchers to enable high-quality integration, validation, and analysis workflows for diseases such as cancer, Alzheimer’s disease, Parkinson’s disease, and cardiovascular disease.

The position is ideal for a candidate with a PhD in computer science, medical informatics, computational biology, bioinformatics, or a closely related field. Required skills include Python programming, experience with machine learning frameworks such as PyTorch, TensorFlow, or Hugging Face, and strong conceptual understanding of clinical and biomedical research infrastructures. Fluency in English at C1 level is required; additional languages are considered an asset. Experience with OHDSI tools, data quality frameworks, GDPR/AI Act topics, EHR systems, and AI/ML-based harmonization tools is advantageous.

The University of Luxembourg offers a modern, multilingual, international environment with strong interdisciplinary collaboration and excellent research infrastructure. The appointment is a fixed-term, full-time contract for 36 months. The annual gross salary for postdoctoral researchers at the University of Luxembourg is EUR 87,306.

To apply, candidates should submit an English CV with publications and projects, a cover letter, PhD diploma or expected defense information, university transcripts, and contact information plus recommendation letters from at least three referees. Applications must be submitted online through the HR system; email applications are not accepted. Early application is encouraged as applications are processed upon receipt.

Funding details

Available

What's required

A PhD in computer science, medical informatics, computational biology, bioinformatics, or a related field is required. Candidates should have hands-on experience with common data models such as OMOP CDM and HL7 FHIR, and with Semantic Web/metadata standards such as HealthDCAT-AP, DPV, and ORDL. Strong programming skills in Python and experience with machine-learning frameworks and libraries such as PyTorch, TensorFlow, or Hugging Face are expected. Applicants should understand clinical and biomedical research, data standards, and research infrastructures, be comfortable working across disciplines, and have fluency in English at C1 level; additional languages are an asset. Desirable experience includes knowledge of the EHDS ecosystem, TEHDAS 2 guidelines, AI programming tools, R, OHDSI tools and packages, data quality frameworks, GDPR and AI Act regulations, clinical datasets, and EHR systems.

How to apply

Prepare an English application with a CV, cover letter, PhD diploma or expected defense information, transcripts, and contact details plus recommendation letters from at least three referees. Apply online through the HR system; email applications will not be considered. Early application is encouraged because applications are processed upon receipt.

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