individuals including for example medication purchases, laboratory measurements, clinical notes and imaging. Your main project will involve building and studying multimodal health trajectories on a nationwide scale to catch increasing disease risk as early as possible.

In addition, this data, and similar datasets from our collaborators across the Nordics, Baltics and Europe present a fantastic opportunity to pursue your own ambitious research goals. Our other research directions of interest include privacy of AI models trained on health data as well as training AI models on health data across national borders.

Key responsibilities

• Design, implement and benchmark machine learning models for large-scale health datasets consisting of diverse information including structured medical history, demographics, clinical notes, laboratory measurements, omics and genetics.
• Collaborate closely with other team members, and national/ international collaborators.
• Assist other team members in experiment planning, data processing and interpretation of results.
• Contribute to writing scientific articles, conference presentations, grant applications and supervision of Master’s students and PhD researchers.
• Take part in open science and code sharing.

Skills, expertise and qualifications

• A PhD degree in computational biology, machine learning, computer science, data science, bioinformatics, or a related discipline
• Demonstrated machine learning experience in form of high-quality scientific publications, experience working with real-world health data is a plus
• Proficiency in Python and experience working in Linux-based HPC environments or cloud computing platforms
• Proven experience with deep learning frameworks such as PyTorch, and familiarity with multimodal data fusion is highly desirable
• Ability to work independently, as well as collaboratively in interdisciplinary and international research teams
• Willingness to supervise junior researchers and develop your supervision skills
• Excellent command of spoken and written English