The Luxembourg Institute of Health (LIH) is seeking a highly motivated Data Scientist in AI with strong expertise in immunological data analysis and one or several of the following data types: multi-omics (e.g., RNA-seq, DNA methylation, proteomics), single-cell technologies (CyTOF, scRNA-seq), structural biology and computational immunology approaches.
The successful candidate will support the expanding research activities at the Department of Infection and Immunity (DII) and the Department of Medical Informatics (DMI) with a particular emphasis on high-throughput, reproducible, service-oriented bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how the immune system develops, functions, and responds to life experiences. In this research associated position you'll bring AI/ML expertise to multiple research groups, helping immunologists leverage state-of-the-art computational methods they couldn't otherwise access. You'll be the AI/ML specialist who makes cutting-edge methods accessible and applicable to biological discovery.

Key Accountabilities

• Support all the DII research groups with AI/ML approaches and implementations
• Work with immunologists to understand their questions and determine which AI/ML approaches are appropriate
• Develop, adapt, and deploy machine learning and deep learning models (transformers, large language models) for immunological data (biological sequences, single-cell data, and protein structures, virtual drug screening)
• Use neural networks to predict immune cell states, perturbation responses, and disease outcomes
• Stay current with the latest AI/ML developments and evaluate their applicability to immunology
• Adapt methods from computer vision, NLP, and other AI domains to biological problems
• Build computational frameworks that integrate multi-scale immune data for digital twin development
• Implement rigorous model validation, interpretation, and biological evaluation
• Create interactive tools that make AI/ML results accessible to non-computational researchers
• Ensure reproducibility and transparency in all AI/ML applications
• Perform literature surveillance for emerging AI/ML methods relevant to biology
• Train researchers in AI/ML fundamentals and best practices
• Innovative use of novel architectures, approaches and combination of tools

Key Skills, Experience and Qualifications

• PhD in biology/biochemistry or minimum MSc in Computer Science with a clear biological application
• Broad interest in biology and an understanding of immunology fundamentals (immune cells, data types, assays)
• Proven experience of applying AI/ML methods to complex, real-world biological problems generating interpretable, biologically meaningful models
• Strong foundation in machine learning theory and practice: you understand not just how to use tools, but how they work
• Deep learning expertise with modern frameworks (PyTorch, TensorFlow, JAX)
• Experience developing, training, and validating ML/DL models (not just applying existing tools)
• Understanding of model interpretation, evaluation metrics, and validation strategies
• Experience with large-scale data processing and high-dimensional datasets
• Ability to create reproducible workflows and well-documented code
• Excellent communication skills—you can explain complex AI/ML concepts to biologists
• Enthusiastic team player interested in working in a collaborative interdisciplinary environment and learning from domain experts
• Service-oriented approach—you enjoy helping others succeed with your expertise
• Fluent English