Data Scientist in AI - Department of Precision Health

The Luxembourg Institute of Health (LIH) is seeking a highly motivated Data Scientist with strong expertise in one or several of the following data types: biomedical signals (e.g., voice, wearables, images), clinical data, and text.
The successful candidate will support the expanding research activities at the Department of Precision Health (DoPH) and the Department of Medical Informatics (DMI) with a particular emphasis on the multimodal integration of structured and unstructured data. They will contribute to research projects aimed at advancing precision health, disease prevention, and population-level health monitoring. Working within a multidisciplinary DMI team and in close collaboration with DoPH researchers, the Data Scientist will engage in cutting-edge research and applied projects using machine learning, deep learning, and biomedical data analysis.

Key Accountabilities

• Support research groups in the planning and implementation of AI-driven analyses of biomedical data, ensuring methodological rigor and reproducibility.
• Develop, train, and validate machine learning and deep learning models for the analysis of structured and unstructured medical data.
• Contribute to the design and development of end-to-end AI pipelines, from data preprocessing and annotation to model deployment and evaluation.
• Collaborate on research projects by analyzing data, visualizing results, and contributing to scientific publications.
• Work closely with clinicians, epidemiologists, biologists, biostatisticians, and computer scientists to translate research findings into real-world healthcare applications.
• Contribute to the training of LIH staff members and PhD students.

Key Skills, Experience and Qualifications

• Master’s or PhD degree in computer science, biomedical engineering, data science or a related field.
• At least 2 years of experience in a similar position.
• Experience in handling structured and unstructured data from diverse sources including, but not limited to clinical data, biomedical signals/images, and medical texts.
• Strong programming skills in Python. Knowledge of R is considered an asset.
• Deep understanding of machine learning techniques and AI algorithms.
• Proficiency with modern deep learning frameworks, such as PyTorch and TensorFlow.
• Experience working in high-performance computing (HPC) environments, including the use of cluster computing, job schedulers (Slurm), and containerization tools (Singularity, Docker), is considered an asset.
• Excellent problem-solving, organizational, and time-management skills.
• Strong communication skills and ability to work effectively in a team and in close collaboration with clinicians, epidemiologists, and/or biologists.
• Self-motivated, team spirit, and service-oriented mindset.
• Language skills: fluent command of English. Knowledge of French and/or German is considered an advantage.