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 the field of Systems Biology and Biomedicine in the lab, in the clinic and in silico. We focus on neurodegeneration and are especially interested in 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 more than 50 countries currently work at the LCSB. We excel because we are truly interdisciplinary and together, we contribute to science and society. Successful candidates will join the Bioinformatics Core, led by Prof. Reinhard Schneider, which focuses on managing and analysing complex biomedical and clinical data. We are internationally recognized for our GDPR compliant data hosting solutions and data management systems. We develop innovative methodologies for data mining, federated data analysis, and data FAIRification. We strongly advocate following responsible and reproducible research (R3) principles and best practices in software development. For more information, please visit our website. is integral part of the CLINNOVA project, an international initiative of 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 harnessing the power of data federation, standardization, and interoperability to advance precision medicine for treatment decisions. To learn more about the CLINNOVA project and its objectives, 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 tailored for health research. You will apply AI/ML algorithms to analyse a diverse range of data types, including clinical, molecular ( omics), and (sensor/mobile and PROMs/PREMs) within a federated environment. Additionally, you will innovate state of the art federated AI/ML methods, to ensure privacy and data security in clinical research. To augment federated analysis, you will be generating synthetic data using ML techniques, such as Generative Adversarial Networks (GANs). Your workflows and methods will be incorporated by a multidisciplinary team into the CLINNOVA platform for federated data management and analysis. You will take an active role on project activities and effectively disseminating findings to the project members and the scientific community through project meeting, conferences and publications. Your main tasks will include: Develop federated analytical workflows : integrate and adapt federated learning workflows specifically designed for health research, emphasizing scalability, efficiency, and pri