Data Scientist in AI - Department of Cancer Research

The Luxembourg Institute of Health (LIH) is seeking a highly motivated Data Scientist in AI with strong expertise in one or several of the following data types: multi-omics (e.g., DNA-seq, RNA-seq, proteomics), single-cell technologies, and foundation models in biomedicine.
The successful candidate will support the expanding research activities at the Department of Cancer Research (DoCR) and the Department of Medical Informatics (DMI) with a particular emphasis on high-throughput, reproducible, service-oriented bioinformatics for cancer research programs, with a strong focus on sequences, multi-omics data, and single-cell datasets. In collaboration with DoCR researchers, she/he will engage in cutting-edge research and applied projects using machine learning, deep learning, and omics data analysis

Key Accountabilities

• Support research groups in the planning and implementation of AI-driven analyses of molecular data, focusing on single-cell and bulk multi-omics and long-read sequencing.
• Develop, train, and validate machine learning and deep learning models for multi-omics integration to learn the shared and modality-specific representations across multiple data types.
• Use pre-trained foundation models developed for biological sequences or single-cell and bulk omics. Fine-tune large models for specific tasks, e.g., variant effect prediction, cell state representation, annotation, perturbation prediction, and classification.  
• Generative AI for omics: develop and apply probabilistic generative models (e.g., VAEs and related approaches) for modeling omics data.
• Implement and maintain scalable pipelines for protein structure prediction, including state-of-the-art tools such as AlphaFold. Perform digital drug screening with the existing tools.
• Work closely with biologists, clinicians, biostatisticians, and computer scientists, support their AI/ML needs, and translate research into real-world applications.
• Contribute to the training of LIH staff members and PhD students.

Key Skills, Experience and Qualifications

• MSc/PhD degree in computer science, biomedical engineering, data science or related.
• At least 2 years of experience in a similar position.
• Expertise in AI/ML and deep learning methods, with a rigorous approach to model evaluation and validation. Experience in handling and understanding omics data.
• Strong programming skills in Python. Knowledge of R is considered an asset.
• Proficiency with modern deep learning frameworks, such as PyTorch and TensorFlow.
• Experience working in high-performance computing (HPC) environments: use of cluster computing, job schedulers, and containerization.
• Excellent problem-solving, organizational, and time-management skills.
• Strong communication skills and ability to work effectively in a team and in close collaboration with biologists and clinicians.
• Self-motivated, team spirit, and service-oriented mindset.
• Language skills: fluent command of English. Knowledge of French and/or German is considered an advantage.