About us...

The Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre of the University of Luxembourg. We conduct fundamental and translational research in Systems Biology and Biomedicine, both in the lab and in silico. Our primary focus is on neurodegeneration, particularly Alzheimer's and Parkinson's disease, and their contributing factors.

The LCSB recruits talented scientists from various disciplines. Computer scientists, mathematicians, biologists, chemists, engineers, physicists, and clinicians from over 50 countries currently work at the LCSB. Our interdisciplinary approach allows us to excel and contribute significantly to science and society.

Successful candidates will join the Bioinformatics Core, led by Prof. Reinhard Schneider, which focuses on managing and analyzing complex biomedical and clinical data. We are internationally recognized for our GDPR-compliant data hosting solutions and data management systems. Our innovative methodologies include data mining, federated data analysis, and data FAIRification. We advocate for responsible and reproducible research (R3) principles and best practices in software development. For more information, please visit our website.

The LCSB is an integral part of the CLINNOVA project, an international initiative involving leading clinicians and scientists from university hospitals, private clinics, and health research institutes across Luxembourg, France, Germany, and Switzerland. The project aims to revolutionize healthcare by leveraging data federation, standardization, and interoperability to advance precision medicine for treatment decisions. To learn more about the CLINNOVA project, visit: https://www.uni.lu/fr/news/clinnova-to-launch-precision-medicine-initiative-across-europe/

Your Role...

As a Postdoctoral Researcher, you will develop and implement federated analytical workflows for health research. You will apply AI/ML algorithms to analyze diverse data types, including clinical, molecular (-omics), and real-world data (sensor/mobile and PROMs/PREMs) within a federated environment. You will also innovate federated AI/ML methods to ensure privacy and data security in clinical research. Additionally, you will generate synthetic data using ML techniques like Generative Adversarial Networks (GANs) to augment federated analysis. Your workflows and methods will be integrated into the CLINNOVA platform for federated data management and analysis. You will actively participate in project activities and disseminate findings to project members and the scientific community through meetings, conferences, and publications. Your main tasks will include:

• Develop federated analytical workflows: Integrate and adapt federated learning workflows for health research, emphasizing scalability, efficiency, and privacy.
• Analyze diverse data sets with AI/ML: Apply advanced AI/ML algorithms to a broad spectrum of health data, including clinical, molecular (-omics), and real-world data, in a federated context.
• Generate and use synthetic data: Create synthetic data using methods like GANs for federated analysis, ensuring the data is realistic and privacy-compliant.
• Support the development of federated data management and analysis platform: Engage with the platform development team to implement federated analytical workflows into the CLINNOVA platform.
• Take an active role in project activities: Lead specific project activities, collaborating with a multidisciplinary team to achieve project goals.
• Disseminate research findings: Share ongoing work and findings with project members, the scientific community, and other stakeholders through meetings, conferences, and publications.

What we expect from you…

Required qualifications:

• A PhD in computer science, information technology, computational biology, bioinformatics, or a related field, with a keen interest in health research and related IT infrastructure.
• Domain knowledge:
  • Good understanding of statistical analysis principles and AI/ML techniques in both centralized and federated environments.
  • Hands-on experience in developing, deploying, and maintaining ML operations (MLOps) within IT infrastructure, including familiarity with virtualization and containerization technologies such as Docker and Kubernetes, is considered advantageous.
• Technical skills:
  • Proficiency in Python programming, including data manipulation libraries (e.g., Pandas), ML frameworks (e.g., scikit-learn), and visualization tools (e.g., Matplotlib, Seaborn).
  • Familiarity with federated technologies, such as Flower and NVIDIA FLARE, is considered advantageous.
• Additional skills:
  • Good ability to manage tasks effectively to meet project deadlines and reporting.
  • Experience with authentication and authorization solutions (e.g., ELIXIR-AAI, OIDC, GA4GH), cloud-based AI/ML services, and testing methodologies (unit, integration, e2e) is considered advantageous.

Here's what awaits you at the LCSB...

• Excellent work environment with state-of-the-art infrastructure, laboratory, and administrative support.
• Truly connected. We collaborate with hospitals and research institutes on national and international levels, as well as industrial partners. Our connection between science and society is vital. From our school lab, the Scienteens Lab, to various outreach activities and partnerships with patient associations, we strive to address society's needs and share our passion for science.
• Be part of a multicultural team. With over 50 nationalities at the LCSB, we organize team-building events, networking activities, and more throughout the year.

Find out more about us!

How to apply...

Applications (in English) should be submitted online and include:

• A detailed curriculum vitae (CV) including a list of publications and projects.
• A cover letter describing experience and future interests.
• Contact information and recommendation letters from at least three referees.

Early application is highly encouraged, as applications will be processed upon reception. Applications by email will not be considered.

The University of Luxembourg embraces inclusion and diversity as key values. We are committed to removing any discriminatory barrier related to gender and beyond in the recruitment and career progression of our staff.

General information:

• Contract type: Fixed Term Contract 36 Months (extension possible).
• Work hours: Full Time 40.0 Hours per Week.
• Location: Belval.
• Job reference: UOL06363.

The yearly gross salary for every Postdoctoral Researcher at the UL is EUR 83099 (full time).