PhD Position in Mechanism-Informed Multimodal AI

General Information

The ARTORG Center for Biomedical Engineering Research is the University of Bern's transdisciplinary Center of Excellence for medical technology research. Its mission is to tackle unmet clinical needs and envision future diagnosis, monitoring, and treatment challenges to create viable healthcare technology solutions with imagination,
agility, and purpose. Its projects run from discovery and basic research to clinical translation.

The Artificial Intelligence in Health and Nutrition (AIHN) laboratory of the ARTORG Center has opened one Ph.D. student position in mechanism-informed multimodal AI models. The successful candidate will contribute to the development of next-generation AI methods integrating mechanistic knowledge with data-driven approaches within a large international research consortium. The duties of the successful candidate include interdisciplinary collaboration and research in the following topics:

• Development of mechanism-informed multimodal AI models
• Mechanism formalisation and discovery using knowledge-driven, data-driven, and hybrid approaches
• Causal inference and modelling (e.g., Structural, Temporal, and Dynamic Causal Models)

The candidates will be affiliated with the University of Bern as PhD students. The positions are funded for up to 4 years. Salary will be according to Swiss University regulations. The lab offers an international environment and the possibility to conduct excellent research. The PhD project is part of a larger, international consortium and requires close collaboration with engineers, computer scientists, healthcare professionals, as well as with industrial partners.

The University of Bern is located at the heart of Switzerland. Internationally connected and regionally anchored, it cultivates exchange with society and strengthens partnerships between science, medicine, business, and politics.The University of Bern is committed to a deliberate and ethical responsibility towards people, animate and inanimate nature. As an important educator, promoting enterprise and industry in the region and beyond, it distinguishes itself through problem-oriented research into questions of pressing social relevance. The University of Bern is an equal opportunity employer, promotes healthy work-life-balance and safe working environments, and strives to increase the number of women at all levels in its faculties.

Requirements

• MSc in computer science, engineering, applied mathematics or related field
• Strong background in machine learning
• Solid understanding of mathematical modelling, probability, and optimization
• Experience in Python and deep learning frameworks (e.g., PyTorch)
• Excellent command of English
• Commitment to multidisciplinary research

Preferred Qualifications

• Experience with causal inference methods (e.g., SCMs, Bayesian networks)
• Knowledge of dynamical systems or systems biology
• Experience with multimodal biomedical data
• Familiarity with knowledge graphs and ontologies
• Experience with generative AI models (e.g., VAEs, diffusion models, multimodal transformers)