Postdoctoral Fellow in AI for Multi-Omics Data Analysis

The Mer Lab ( merlab.github.io/) at the University of Ottawa, Canada, is seeking a highly motivated postdoctoral fellow to develop machine learning and AI methods for large-scale biomedical data analysis, with a focus on multi-omics, precision medicine, and human disease.

The successful candidate will work at the intersection of bioinformatics, machine learning, artificial intelligence, and personalized medicine. The position is based in the Faculty of Medicine at the University of Ottawa, with affiliation to the School of Electrical Engineering and Computer Science. The postdoctoral fellow will join a vibrant and rapidly growing research environment with excellent opportunities for interdisciplinary collaboration in AI, medicine, omics, and computational biology.

Ottawa, Canada’s capital, is a multicultural and bilingual city known for its high quality of life, green spaces, cultural activities, and proximity to Montréal and Toronto.

The postdoctoral fellow will develop and apply AI and machine learning approaches for integrative analysis of large biomedical datasets. This includes:

• Multi-omics data integration and analysis
• Deep learning and AI method development for biomedical applications
• Integration of omics data with histopathology image data
• Explainable AI for precision medicine
• Development of computational tools for disease diagnosis, prognosis, and patient stratification
• The candidate will be expected to design and implement computational methods, analyze large-scale datasets, collaborate with experimental and clinical researchers, prepare manuscripts, and contribute to research presentations and grant applications.

• A PhD completed or near completion in bioinformatics, computational biology, computer science, data science, engineering, statistics, or a related field
• Strong programming skills, preferably in Python and/or C/C++
• Experience with machine learning, deep learning, or AI model development
• Strong analytical and problem-solving skills
• Excellent communication and scientific writing skills in English
• Motivation, independence, and enthusiasm for interdisciplinary research
• Experience in multi-omics data analysis, genomics, biomedical image analysis, explainable AI, high-performance computing, or molecular biology is an asset but not required.